TCC
Leonardo Fernandes Wink
25/09/2022
1 Brief explanation
Every boxplot means a monitoring point (Ponto de monitoramento (or PM) in portuguese). My goal here is to analyze the evolution between decades of each water quality parameter that compounds the Water Quality Index (WQI).
The river flows in the east-west direction as shown in the image below.
The logic behind the sorting in the boxplots is because of 2 main reasons:
- The original monitoring point isn’t easy to understand (8 digits, like 87409900)
- Changing the original nomenclature to PM1, PM2 (…) makes it easier to understand that the last point has water contributions of every other point upstream.
Some features that I want to add: * If the parameter is x, then use x’s classes (with its own classes background color plotted) * Define the timescale, should act just like a filter
# plan_wide_19902020 %>%
# filter(ANO_COLETA > "1990" &
# ANO_COLETA <= "2000")2 Anotações de coisas por fazer:
- Descobrir como colocar as estações no sentido correto montante -> jusante nos sumários
87398500, 87398980, 87398900, 87398950, 87405500, 87406900, 87409900
Aprender a segmentar o meu dataset por períodos- aprender a criar uma nova coluna com a segmentação dos períodos
- maybe use
~facet.grid - aprender a colocar a legenda dentro do gráfico
- reduzir o tamanho da legenda
corrigir os valores 0 de IQA pra NA- descobrir como conseguir a equação do lm
aprender a pivotar o sumário-> meu sumário do google docs ta batendo direitinho com o do R- descobrir se há outros TCCs com disponibilização de códigos
Namontá com com casa decimal","eptottá com"."- correlação forte entre condutividade e Namon/Ptot/DBO
| 1990-2000 | 2000-2010 | 2010-2020 |
|---|---|---|
| 1990-2000 | 2000-2010 | 2010-2020 |
3 Instalar os pacotes
# install.packages(tidyverse)3.1 acessar os pacotes
# library(readr)
# library(rmarkdown)
# # library(qboxplot)
# library(readxl)
# library(pillar)
# library(dplyr)
# library(tidyverse)
# library(gapminder)
# library(knitr)
# library(kableExtra)
# library(ggpubr)
# library(gridExtra)
# library(modelsummary)
# library(gtsummary)
# library(GGally)
pacman::p_load(readr, rmarkdown, readxl,
pillar, dplyr, tidyverse,
gapminder, knitr, kableExtra,
gridExtra, #modelsummary,
gtsummary, ggplot2,
ggbeeswarm, GGally)
# pacman::p_load(tibbletime)knitr::knit_hooks$set(time_it = local({
now <- NULL
function(before, options) {
if (before) {
# record the current time before each chunk
now <<- Sys.time()
} else {
# calculate the time difference after a chunk
res <- difftime(Sys.time(), now)
# return a character string to show the time
paste("Time for this code chunk to run:", res)
}
}
}))
knitr::opts_chunk$set(time_it = TRUE)3.2 importando a planilha
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4 data wrangling
# Como há dados faltantes, no cálculo entre o produto das colunas, ele acaba interpretando como se fosse zero, mas na verdade é NA
plan_wide_19902020 <- plan_wide_19902020 %>%
mutate(IQA = ifelse(IQA == 0, NA, IQA))
parametros_IQA <- plan_wide_19902020 %>%
select(CODIGO,
pH,
DBO,
`Escherichia coli`,
`Nitrogênio amoniacal`,
`Nitrogênio total`,
`Fósforo total`,
`Temperatura água`,
Turbidez,
`Sólidos totais`,
`Oxigênio dissolvido`,
Condutividade)
write.csv(parametros_IQA,
"./parametros_IQA.csv",
row.names = FALSE)Time for this code chunk to run: 0.0501639842987061
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5 setting theme
theme_grafs <- function(bg = "white",
coloracao_letra = "black") {
theme(
plot.title =
element_text(
hjust = 0.5,
color = coloracao_letra,
size = 19),
axis.title.x =
# element_text(
# color = coloracao_letra,
# size = 15,
# angle = 0,),
element_blank(),
axis.title.y = element_text(
color = coloracao_letra,
size = 15,
angle = 90),
axis.text.x = element_text(
color = coloracao_letra,
size = 17),
axis.text.y = element_text(
color = coloracao_letra,
size = 17,
angle = 0),
strip.background = element_rect(fill = bg,
linetype = 1,
size = 0.5,
color = "black"),
panel.background = element_rect(fill = bg),
plot.background = element_rect(fill = bg),
plot.margin = margin(l = 5, r = 10,
b = 5, t = 5)
)
}Time for this code chunk to run: 0.00703191757202148
6 setting different timescales
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7 setting sumaries
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8 Parâmetros físico-químicos
8.0.1 Oxigênio Dissolvido
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grid.arrange(od_p1, od_p2, od_p3, ncol = 3)
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chunk to run: 1.40598917007446
ggsave("od.png",
units = c("px"),
width = 4500,
height = 2993,
plot = od,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("od_p1.png",
plot = od_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("od_p2.png",
plot = od_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("od_p3.png",
plot = od_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("od_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(od_p1, od_p2, od_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time for
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grid.arrange(iqaod_p1, iqaod_p2, iqaod_p3, ncol = 3)
Time
for this code chunk to run: 1.70442891120911
## # A tibble: 7 x 8
## par `87398500` `87398900` `87398950` `87398980` `87405500` 874069~1 87409~2
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 min 0.8 2 2.5 4.2 0.1 0.1 0.1
## 2 q1 4.9 5.6 4.4 6 1.9 0.25 1.4
## 3 median 6.4 6.9 5.95 6.3 4.2 2.6 2.9
## 4 mean 5.99 6.78 5.98 7.01 4.22 2.98 3.60
## 5 q3 7.3 8 7.1 8.2 6 5 5.65
## 6 max 10.8 10.5 10.3 12.1 19.9 10.2 11.1
## 7 n 101 101 68 30 97 32 65
## # ... with abbreviated variable names 1: `87406900`, 2: `87409900`## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.4 3.5 4.9 5.01 6.65 10.9
## 2 87398900 1.9 4 5.5 5.33 6.6 12
## 3 87398950 1.7 3.2 5.3 5.06 6.18 8.9
## 4 87398980 1.2 3.8 5.6 5.38 6.6 9.2
## 5 87405500 0.2 1.4 2.55 3.28 4 14.2
## 6 87406900 0 1.1 1.9 2.59 3.15 16
## 7 87409900 0 0.7 2.3 3.12 3.7 10.6## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.38 3.11 4.41 4.57 6.2 12.4
## 2 87398900 3.52 5.25 5.96 6.61 7.3 13.8
## 3 87398950 1.62 3.68 4.92 5.28 6.64 11.9
## 4 87398980 3.37 5.5 6.17 6.48 7.14 13.1
## 5 87405500 0.2 1.3 2.53 2.83 3.66 9.8
## 6 87406900 0.1 0.865 2.4 2.43 3.05 9.1
## 7 87409900 0.1 0.92 2.03 2.43 3.5 8.1Time for this code chunk to run: 0.184609889984131
8.0.2 Demanda Bioquímica de Oxigênio
(dbo <- ggplot(plan_wide_19902020,
aes(x = CODIGO,
y = DBO))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=10,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=5,
ymax=10,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3,
ymax=5,
alpha=1,
fill="#70c18c")+ #classe 2
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=3,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Demanda Bioquímica de Oxigênio no período 1990-2020",
x="Estação",
y="mg/L")+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
n.breaks = 8,
limits = c(1,100),
trans = "log10")+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)## Warning: Transformation introduced infinite values in continuous y-axis## Warning: Removed 60 rows containing non-finite values (stat_boxplot).
## Removed 60 rows containing non-finite values (stat_boxplot).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 22 rows containing missing values (position_quasirandom).## Warning: Removed 30 rows containing missing values (position_quasirandom).## Warning: Removed 8 rows containing missing values (position_quasirandom).
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grid.arrange(dbo_p1, dbo_p2, dbo_p3, ncol = 3)
Time
for this code chunk to run: 1.4840681552887
(sum_dbo_p1 <- plan_wide_19902020 %>%
select(CODIGO, DBO, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(DBO,
na.rm = TRUE),
q1 =
quantile(DBO, 0.25,
na.rm = TRUE),
median =
median(DBO,
na.rm = TRUE),
mean =
mean(DBO,
na.rm= TRUE),
q3 =
quantile(DBO, 0.75,
na.rm = TRUE),
max =
max(DBO,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 1 1 2 1.86 2 13
## 2 87398900 1 1 1 1.52 2 6
## 3 87398950 1 1 1 1.66 2 6
## 4 87398980 1 1 1 1.13 1 2
## 5 87405500 1 2 3 5.37 5 64
## 6 87406900 1 4 5 9 11 26
## 7 87409900 2 3 4 6.97 9.5 31(sum_dbo_p2 <- plan_wide_19902020 %>%
select(CODIGO, DBO, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(DBO,
na.rm = TRUE),
q1 =
quantile(DBO, 0.25,
na.rm = TRUE),
median =
median(DBO,
na.rm = TRUE),
mean =
mean(DBO,
na.rm= TRUE),
q3 =
quantile(DBO, 0.75,
na.rm = TRUE),
max =
max(DBO,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 1 1 1 1.58 2 5
## 2 87398900 1 1 1 1.40 2 5
## 3 87398950 1 1 1 1.66 2 5
## 4 87398980 1 1 1 1.30 1 5
## 5 87405500 1 2 4 4.67 6.5 14
## 6 87406900 1 3 5 6.53 8 28
## 7 87409900 1 3 6 6.31 9 15(sum_dbo_p3 <- plan_wide_19902020 %>%
select(CODIGO, DBO, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(DBO,
na.rm = TRUE),
q1 =
quantile(DBO, 0.25,
na.rm = TRUE),
median =
median(DBO,
na.rm = TRUE),
mean =
mean(DBO,
na.rm= TRUE),
q3 =
quantile(DBO, 0.75,
na.rm = TRUE),
max =
max(DBO,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 1 1 1.5 2.15 3 7
## 2 87398900 1 1 1 1.51 2 5
## 3 87398950 1 1 2 2.65 2 18
## 4 87398980 1 1 1 1.32 2 2
## 5 87405500 1 3 4 5.28 6.25 21
## 6 87406900 1 3 5 6.58 10 24
## 7 87409900 1 3 4.5 6.18 8 18Time for this code chunk to run: 0.154015064239502
ggsave("dbo.png",
units = c("px"),
width = 4500,
height = 2993,
plot = dbo,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("dbo_p1.png",
plot = dbo_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("dbo_p2.png",
plot = dbo_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("dbo_p3.png",
plot = dbo_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("dbo_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(dbo_p1, dbo_p2, dbo_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.45231294631958
8.0.3 Fósforo total
(ptot <- ggplot(plan_wide_19902020,
aes(CODIGO,
`Fósforo total`))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.15,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.1,
ymax=0.15,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=0.1,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Fósforo total no período 1990-2020",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$`Fósforo total`, na.rm = TRUE),
max(plan_wide_19902020$`Fósforo total`), na.rm = TRUE),
trans = "log10")+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)## Warning: Transformation introduced infinite values in continuous y-axis## Warning: Removed 134 rows containing non-finite values (stat_boxplot).
## Removed 134 rows containing non-finite values (stat_boxplot).## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 47 rows containing missing values (position_quasirandom).## Warning: Removed 31 rows containing missing values (position_quasirandom).## Warning: Removed 56 rows containing missing values (position_quasirandom).
Time
for this code chunk to run: 1.27888202667236
(ptot_p1<-ggplot(plan_wide_19902020%>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000"),
aes(CODIGO,
`Fósforo total`))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.15,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.1,
ymax=0.15,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=0.1,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Fósforo total no período 1990-2000",
x="Estação",
y="mg/L")+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$`Fósforo total`, na.rm = TRUE),
max(plan_wide_19902020$`Fósforo total`), na.rm = TRUE),
trans = "log10")+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.550328016281128
(ptot_p2 <- ggplot(plan_wide_19902020%>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
`Fósforo total`))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.15,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.1,
ymax=0.15,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=0.1,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Fósforo total no período 2000-2010",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$`Fósforo total`, na.rm = TRUE),
max(plan_wide_19902020$`Fósforo total`), na.rm = TRUE),
trans = "log10")+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.645510196685791
(ptot_p3 <- ggplot(plan_wide_19902020%>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
`Fósforo total`))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.15,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0.1,
ymax=0.15,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=0.1,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Fósforo total no período 2010-2020",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$`Fósforo total`, na.rm = TRUE),
max(plan_wide_19902020$`Fósforo total`), na.rm = TRUE),
trans = "log10")+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.484117984771729
grid.arrange(ptot_p1, ptot_p2, ptot_p3, ncol = 3)
Time
for this code chunk to run: 1.51988220214844
(sum_ptot_p1 <- plan_wide_19902020 %>%
select(CODIGO, `Fósforo total`, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(`Fósforo total`, na.rm = TRUE),
q1 =
quantile(`Fósforo total`, 0.25, na.rm = TRUE),
median =
median(`Fósforo total`, na.rm = TRUE),
mean =
mean(`Fósforo total`, na.rm= TRUE),
q3 =
quantile(`Fósforo total`, 0.75, na.rm = TRUE),
max =
max(`Fósforo total`, na.rm = TRUE)))## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.0097 0.0593 0.0881 0.123 0.14 0.863
## 2 87398900 0.0023 0.0468 0.0678 0.0747 0.0883 0.247
## 3 87398950 0.0202 0.0544 0.0737 0.0751 0.0904 0.179
## 4 87398980 0.01 0.0254 0.0547 0.0708 0.114 0.189
## 5 87405500 0.017 0.171 0.281 0.417 0.492 2.32
## 6 87406900 0.156 0.270 0.508 0.785 1.07 2.79
## 7 87409900 0.107 0.258 0.384 0.489 0.712 1.53(sum_ptot_p2 <- plan_wide_19902020 %>%
select(CODIGO, `Fósforo total`, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(`Fósforo total`, na.rm = TRUE),
q1 =
quantile(`Fósforo total`, 0.25, na.rm = TRUE),
median =
median(`Fósforo total`, na.rm = TRUE),
mean =
mean(`Fósforo total`, na.rm= TRUE),
q3 =
quantile(`Fósforo total`, 0.75, na.rm = TRUE),
max =
max(`Fósforo total`, na.rm = TRUE)))## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.025 0.094 0.131 0.148 0.16 0.637
## 2 87398900 0.015 0.0764 0.104 0.140 0.164 0.646
## 3 87398950 0.036 0.116 0.171 0.180 0.207 0.485
## 4 87398980 0.0115 0.052 0.076 0.101 0.103 1
## 5 87405500 0.046 0.261 0.406 0.547 0.681 1.98
## 6 87406900 0.056 0.338 0.599 0.752 0.967 3.49
## 7 87409900 0.043 0.325 0.624 0.677 0.989 1.57(sum_ptot_p3 <- plan_wide_19902020 %>%
select(CODIGO, `Fósforo total`, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(`Fósforo total`, na.rm = TRUE),
q1 =
quantile(`Fósforo total`, 0.25, na.rm = TRUE),
median =
median(`Fósforo total`, na.rm = TRUE),
mean =
mean(`Fósforo total`, na.rm= TRUE),
q3 =
quantile(`Fósforo total`, 0.75, na.rm = TRUE),
max =
max(`Fósforo total`, na.rm = TRUE)))## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.061 0.118 0.163 0.166 0.186 0.381
## 2 87398900 0.057 0.0935 0.130 0.163 0.168 0.444
## 3 87398950 0.07 0.132 0.156 0.292 0.221 3.11
## 4 87398980 0.019 0.0625 0.106 0.144 0.170 0.59
## 5 87405500 0.013 0.187 0.332 0.361 0.45 0.803
## 6 87406900 0.089 0.254 0.364 0.448 0.560 1.26
## 7 87409900 0.203 0.259 0.369 0.488 0.564 1.7Time for this code chunk to run: 0.169561147689819
ggsave("ptot.png",
units = c("px"),
width = 4500,
height = 2993,
plot = ptot,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ptot_p1.png",
plot = ptot_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ptot_p2.png",
plot = ptot_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ptot_p3.png",
plot = ptot_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ptot_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(ptot_p1, ptot_p2, ptot_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.4768168926239
8.0.4 Escherichia coli
(ecoli <- ggplot(plan_wide_19902020,
aes(CODIGO,
`Escherichia coli`))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3200,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=800,
ymax=3200,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=160,
ymax=800,
alpha=1,
fill="#70c18c")+ #classe 2
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=160,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Escherichia coli no período 1990-2020",
x="Estação",
y="NMP/100mL")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE),
max(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 1.33779001235962
(ecoli_p1 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000"),
aes(CODIGO,
`Escherichia coli`))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3200,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=800,
ymax=3200,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=160,
ymax=800,
alpha=1,
fill="#70c18c")+ #classe 2
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=160,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Escherichia coli no período 1990-2000",
x="Estação",
y="NMP/100mL")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE),
max(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.613343954086304
(ecoli_p2 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
`Escherichia coli`))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3200,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=800,
ymax=3200,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=160,
ymax=800,
alpha=1,
fill="#70c18c")+ #classe 2
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=160,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Escherichia coli no período 2000-2010",
x="Estação",
y="NMP/100mL")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE),
max(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.547337055206299
(ecoli_p3 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
`Escherichia coli`))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3200,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=800,
ymax=3200,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=160,
ymax=800,
alpha=1,
fill="#70c18c")+ #classe 2
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=160,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Escherichia coli no período 2010-2020",
x="Estação",
y="NMP/100mL")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE),
max(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.690122127532959
grid.arrange(ecoli_p1, ecoli_p2, ecoli_p3, ncol = 3)
Time
for this code chunk to run: 1.56988191604614
(sum_ecoli_p1 <- plan_wide_19902020 %>%
select(CODIGO, `Escherichia coli`, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(`Escherichia coli`,
na.rm = TRUE),
q1 =
quantile(`Escherichia coli`, 0.25,
na.rm = TRUE),
median =
median(`Escherichia coli`,
na.rm = TRUE),
mean =
mean(`Escherichia coli`,
na.rm= TRUE),
q3 =
quantile(`Escherichia coli`, 0.75,
na.rm = TRUE),
max =
max(`Escherichia coli`,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 32 136 240 854. 720 19200
## 2 87398900 16 68 160 548. 480 7760
## 3 87398950 2.4 12.8 268 4039. 10000 28000
## 4 87398980 4 160 243. 2907. 446 25600
## 5 87405500 1.6 12.8 24 545. 128 18400
## 6 87406900 13.6 61.6 192 718. 414 12800
## 7 87409900 2.4 12.8 64 97.7 128 720(sum_ecoli_p2 <- plan_wide_19902020 %>%
select(CODIGO, `Escherichia coli`, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(`Escherichia coli`,
na.rm = TRUE),
q1 =
quantile(`Escherichia coli`, 0.25,
na.rm = TRUE),
median =
median(`Escherichia coli`,
na.rm = TRUE),
mean =
mean(`Escherichia coli`,
na.rm= TRUE),
q3 =
quantile(`Escherichia coli`, 0.75,
na.rm = TRUE),
max =
max(`Escherichia coli`,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 21.6 91 150 1335. 308 27200
## 2 87398900 11 70 133. 444. 414. 2600
## 3 87398950 20 400 720 935. 1120 5500
## 4 87398980 24 110. 195 410. 289. 8800
## 5 87405500 4.7 162 2400 25445. 12950 490000
## 6 87406900 8 172 12800 66370. 62300 650000
## 7 87409900 16 7355. 35500 72440. 68750 460000(sum_ecoli_p3 <- plan_wide_19902020 %>%
select(CODIGO, `Escherichia coli`, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(`Escherichia coli`,
na.rm = TRUE),
q1 =
quantile(`Escherichia coli`, 0.25,
na.rm = TRUE),
median =
median(`Escherichia coli`,
na.rm = TRUE),
mean =
mean(`Escherichia coli`,
na.rm= TRUE),
q3 =
quantile(`Escherichia coli`, 0.75,
na.rm = TRUE),
max =
max(`Escherichia coli`,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 90 155. 260 409. 451 2420
## 2 87398900 10 52.8 107 245. 313 1553.
## 3 87398950 108. 250 487 1424. 1553. 10462
## 4 87398980 40.8 140. 242. 529. 738. 2400
## 5 87405500 632 8965 19232. 109992. 70750 1400000
## 6 87406900 1440 23100 34500 230828. 140500 3400000
## 7 87409900 2000 20100 38400 83128. 83680 345000Time for this code chunk to run: 0.158982992172241
ggsave("ecoli.png",
plot = ecoli,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ecoli_p1.png",
plot = ecoli_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ecoli_p2.png",
plot = ecoli_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ecoli_p3.png",
plot = ecoli_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("ecoli_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(ecoli_p1, ecoli_p2, ecoli_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.53750395774841
8.0.5 Nitrogênio amoniacal
(namon <- ggplot(plan_wide_19902020,
aes(CODIGO,
`Nitrogênio total`))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=13.3,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3.7,
ymax=13.3,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=3.7,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Nitrogênio amoniacal no período 1990-2020",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE),
max(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = .001,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 1.3453049659729
(namon_p1 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000"),
aes(CODIGO,
`Nitrogênio total`))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=13.3,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3.7,
ymax=13.3,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=3.7,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Nitrogênio amoniacal no período 1990-2000",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE),
max(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = .001,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.559706926345825
(namon_p2 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
`Nitrogênio total`))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=13.3,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3.7,
ymax=13.3,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=3.7,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Nitrogênio amoniacal no período 2000-2010",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE),
max(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = .001,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.737847805023193
(namon_p3 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
`Nitrogênio total`))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=13.3,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=3.7,
ymax=13.3,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=3.7,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Nitrogênio amoniacal no período 2010-2020",
x="Estação",
y="mg/L")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 9,
limits = c(min(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE),
max(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = .001,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.534795999526978
grid.arrange(namon_p1, namon_p2, namon_p3, ncol = 3)
Time
for this code chunk to run: 1.61600399017334
(sum_namon_p1 <- plan_wide_19902020 %>%
select(CODIGO, `Nitrogênio total`, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(`Nitrogênio total`,
na.rm = TRUE),
q1 =
quantile(`Nitrogênio total`, 0.25,
na.rm = TRUE),
median =
median(`Nitrogênio total`,
na.rm = TRUE),
mean =
mean(`Nitrogênio total`,
na.rm= TRUE),
q3 =
quantile(`Nitrogênio total`, 0.75,
na.rm = TRUE),
max =
max(`Nitrogênio total`,
na.rm = TRUE),
n =
length(`Nitrogênio total`)
)
)## # A tibble: 7 x 8
## CODIGO min q1 median mean q3 max n
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
## 1 87398500 0.44 0.842 1.00 1.22 1.34 3.81 101
## 2 87398900 0.22 0.82 1 1.09 1.25 4.86 101
## 3 87398950 0.51 0.83 1.02 1.06 1.19 2.16 68
## 4 87398980 0.549 0.68 0.755 0.872 1.01 1.85 30
## 5 87405500 0.51 1.53 2.94 5.27 6.77 21.6 97
## 6 87406900 1.34 2.60 4.56 7.58 11.2 29.1 32
## 7 87409900 0.5 1.98 4.29 5.18 7.01 19.6 65(sum_namon_p2 <- plan_wide_19902020 %>%
select(CODIGO, `Nitrogênio total`, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(`Nitrogênio total`,
na.rm = TRUE),
q1 =
quantile(`Nitrogênio total`, 0.25,
na.rm = TRUE),
median =
median(`Nitrogênio total`,
na.rm = TRUE),
mean =
mean(`Nitrogênio total`,
na.rm= TRUE),
q3 =
quantile(`Nitrogênio total`, 0.75,
na.rm = TRUE),
max =
max(`Nitrogênio total`,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.18 0.885 0.992 1.80 1.46 23.2
## 2 87398900 0.48 0.894 1.13 1.38 1.57 7.92
## 3 87398950 0.57 1.26 1.45 1.43 1.71 1.98
## 4 87398980 0.19 0.685 0.79 1.05 1.10 5.2
## 5 87405500 0.968 2 3.29 5.45 6.60 21.7
## 6 87406900 0.77 2.4 4.54 7.30 10.2 39.1
## 7 87409900 1.62 2.5 6.97 7.92 10.6 21.5(sum_namon_p3 <- plan_wide_19902020 %>%
select(CODIGO, `Nitrogênio total`, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(`Nitrogênio total`,
na.rm = TRUE),
q1 =
quantile(`Nitrogênio total`, 0.25,
na.rm = TRUE),
median =
median(`Nitrogênio total`,
na.rm = TRUE),
mean =
mean(`Nitrogênio total`,
na.rm= TRUE),
q3 =
quantile(`Nitrogênio total`, 0.75,
na.rm = TRUE),
max =
max(`Nitrogênio total`,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 0.222 0.89 1.11 1.24 1.41 2.56
## 2 87398900 0.095 0.883 1.02 1.29 1.40 4.25
## 3 87398950 0.612 1.04 1.43 1.90 2.06 9.5
## 4 87398980 0.216 0.973 1.12 1.22 1.58 2.32
## 5 87405500 1.12 2.03 3.14 4.50 5.93 22.0
## 6 87406900 1.37 2.40 5.58 6.47 7.58 25
## 7 87409900 1.11 3 6.15 7.29 7.75 36Time for this code chunk to run: 0.164543867111206
ggsave("namon.png",
units = c("px"),
width = 4500,
height = 2993,
plot = namon,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("namon_p1.png",
plot = namon_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("namon_p2.png",
plot = namon_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("namon_p3.png",
plot = namon_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("namon_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(namon_p1, namon_p2, namon_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.21558594703674
8.0.6 Turbidez
(turb <- ggplot(plan_wide_19902020,
aes(CODIGO,
Turbidez))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=100,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=40,
ymax=100,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=40,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Turbidez no período 1990-2020",
x="Estação",
y="UNT")+
scale_y_continuous(expand = expansion(mult = c(0.05, 0.05)),
n.breaks = 16,
limits = c(min(plan_wide_19902020$Turbidez, na.rm = TRUE),
500
# max(plan_wide_19902020$Turbidez, na.rm = TRUE)
),
# trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
plan_wide_19902020 %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2020") %>%
select(CODIGO, Turbidez, DATA_COLETA) %>%
group_by(CODIGO) %>%
ggplot(aes(x = DATA_COLETA,
y = Turbidez,
# color = Turbidez
))+
geom_point(na.rm = TRUE)+
geom_smooth(
method = "lm",
# formula = y ~ poly(x, 2),
span = 0.2,
se = TRUE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group = 1),
alpha =.5,
na.rm = TRUE,
size = 0.3,
fullrange = TRUE,
show.legend = TRUE
)+
stat_smooth(
geom = "smooth",
# span = 0.2,
se = FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
# aes(group = 1),
# alpha =.5,
na.rm = TRUE,
# size = 0.3,
fullrange = TRUE,
show.legend = TRUE
)+
facet_wrap(
~CODIGO,
nrow = 4,
)+
# scale_x_continuous(expand = expansion(mult = c(0.05, 0.03)))+
theme_bw()
Time
for this code chunk to run: 2.419517993927
(turb_p1 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000"),
aes(CODIGO,
Turbidez))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=100,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=40,
ymax=100,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=40,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Turbidez no período 1990-2000",
x="Estação",
y="UNT")+
scale_y_continuous(expand = expansion(mult = c(0.05, 0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$Turbidez, na.rm = TRUE),
max(plan_wide_19902020$Turbidez, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.554862976074219
(turb_p2 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
Turbidez))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=100,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=40,
ymax=100,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=40,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Turbidez no período 2000-2010",
x="Estação",
y="UNT")+
scale_y_continuous(expand = expansion(mult = c(0.05, 0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$Turbidez, na.rm = TRUE),
max(plan_wide_19902020$Turbidez, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.561656951904297
(turb_p3 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
Turbidez))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=100,
ymax=Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=40,
ymax=100,
alpha=1,
fill="#fcf7ab")+ #classe 3
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=0,
ymax=40,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Turbidez no período 2010-2020",
x="Estação",
y="UNT")+
scale_y_continuous(expand = expansion(mult = c(0.05, 0.03)),
n.breaks = 8,
limits = c(min(plan_wide_19902020$Turbidez, na.rm = TRUE),
max(plan_wide_19902020$Turbidez, na.rm = TRUE)),
trans = "log10",
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.522236108779907
grid.arrange(turb_p1, turb_p2, turb_p3, ncol = 3)
Time
for this code chunk to run: 1.56782102584839
(sum_turb_p1 <- plan_wide_19902020 %>%
select(CODIGO, Turbidez, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(Turbidez,
na.rm = TRUE),
q1 =
quantile(Turbidez, 0.25,
na.rm = TRUE),
median =
median(Turbidez,
na.rm = TRUE),
mean =
mean(Turbidez,
na.rm= TRUE),
q3 =
quantile(Turbidez, 0.75,
na.rm = TRUE),
max =
max(Turbidez,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 6.2 19 34.5 63.5 67 461
## 2 87398900 9 19 49.5 61.5 73.8 460
## 3 87398950 9.6 16 22 33.3 48.8 144
## 4 87398980 16 32.8 43 66.8 90.5 190
## 5 87405500 8.5 23.5 47 47.5 58 159
## 6 87406900 33 54.8 67 77.7 81.5 199
## 7 87409900 5.8 15 25 32.2 48 76(sum_turb_p2 <- plan_wide_19902020 %>%
select(CODIGO, Turbidez, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(Turbidez,
na.rm = TRUE),
q1 =
quantile(Turbidez, 0.25,
na.rm = TRUE),
median =
median(Turbidez,
na.rm = TRUE),
mean =
mean(Turbidez,
na.rm= TRUE),
q3 =
quantile(Turbidez, 0.75,
na.rm = TRUE),
max =
max(Turbidez,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 9 41.2 55.5 71.1 74.2 428
## 2 87398900 39 57 78 107. 116. 475
## 3 87398950 39 47 64 96.5 90 330
## 4 87398980 24 37 50 64.5 87 176
## 5 87405500 32 46 63.5 70.3 76 341
## 6 87406900 35 49 62 69.9 75.5 284
## 7 87409900 40 45 60 70.4 90 151(sum_turb_p3 <- plan_wide_19902020 %>%
select(CODIGO, Turbidez, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(Turbidez,
na.rm = TRUE),
q1 =
quantile(Turbidez, 0.25,
na.rm = TRUE),
median =
median(Turbidez,
na.rm = TRUE),
mean =
mean(Turbidez,
na.rm= TRUE),
q3 =
quantile(Turbidez, 0.75,
na.rm = TRUE),
max =
max(Turbidez,
na.rm = TRUE))
) ## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 8.52 16.4 29 33.3 43 85
## 2 87398900 14.8 39.2 48.3 66.7 73.4 299
## 3 87398950 16 29.9 41 51.6 65 230
## 4 87398980 11 19.4 33.6 39.5 42.2 110.
## 5 87405500 10.0 29.0 41 42.9 54.5 131
## 6 87406900 9.62 23 39 41.2 52 122
## 7 87409900 9.68 22.0 34.0 40.5 47 182.Time for this code chunk to run: 0.166052103042603
ggsave("turb.png",
units = c("px"),
width = 4500,
height = 2993,
plot = turb,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("turb_p1.png",
plot = turb_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("turb_p2.png",
plot = turb_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("turb_p3.png",
plot = turb_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("turb_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(turb_p1, turb_p2, turb_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.44439697265625
8.0.7 pH
(pH <- ggplot(plan_wide_19902020,
aes(CODIGO,
pH))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=6,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=9,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=6,
ymax=9,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "pH no período 1990-2020",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 8,
limits = c(4,11),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 1.39501690864563
(pH_p1 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000"),
aes(CODIGO,
pH))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=6,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=9,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=6,
ymax=9,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "pH no período 1990-2000",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 8,
limits = c(4,11),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.61137580871582
(pH_p2 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
pH))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=6,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=9,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=6,
ymax=9,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "pH no período 2000-2010",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 8,
limits = c(4,11),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.553849935531616
(pH_p3 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
pH))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=6,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=9,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=6,
ymax=9,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "pH no período 2010-2020",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
n.breaks = 8,
limits = c(4,11),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.49193286895752
grid.arrange(pH_p1, pH_p2, pH_p3, ncol = 3)
Time
for this code chunk to run: 1.48677492141724
(sum_pH_p1 <- plan_wide_19902020 %>%
select(CODIGO, pH, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(pH,
na.rm = TRUE),
q1 =
quantile(pH, 0.25,
na.rm = TRUE),
median =
median(pH,
na.rm = TRUE),
mean =
mean(pH,
na.rm= TRUE),
q3 =
quantile(pH, 0.75,
na.rm = TRUE),
max =
max(pH,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 5 6.18 6.59 6.51 6.82 7.9
## 2 87398900 5.2 6 6.3 6.33 6.63 7.9
## 3 87398950 5.4 6.29 6.4 6.49 6.72 8.1
## 4 87398980 5.3 5.93 6.2 6.16 6.3 7.3
## 5 87405500 5 6.3 6.4 6.47 6.7 9.3
## 6 87406900 5.5 6.18 6.45 6.43 6.8 7.3
## 7 87409900 4.5 6.2 6.4 6.44 6.7 7.4(sum_pH_p2 <- plan_wide_19902020 %>%
select(CODIGO, pH, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(pH,
na.rm = TRUE),
q1 =
quantile(pH, 0.25,
na.rm = TRUE),
median =
median(pH,
na.rm = TRUE),
mean =
mean(pH,
na.rm= TRUE),
q3 =
quantile(pH, 0.75,
na.rm = TRUE),
max =
max(pH,
na.rm = TRUE))
) ## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 5.3 6.3 6.6 6.59 6.88 7.9
## 2 87398900 5.5 6.4 6.65 6.63 6.9 7.5
## 3 87398950 6 6.6 6.8 6.89 7.25 7.6
## 4 87398980 5.8 6.3 6.5 6.63 7 7.5
## 5 87405500 5.2 6.4 6.6 6.68 6.9 8.3
## 6 87406900 5.5 6.4 6.7 6.66 6.9 8.6
## 7 87409900 5.8 6.5 6.8 6.77 7 8.4(sum_pH_p3 <- plan_wide_19902020 %>%
select(CODIGO, pH, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(pH,
na.rm = TRUE),
q1 =
quantile(pH, 0.25,
na.rm = TRUE),
median =
median(pH,
na.rm = TRUE),
mean =
mean(pH,
na.rm= TRUE),
q3 =
quantile(pH, 0.75,
na.rm = TRUE),
max =
max(pH,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 5.47 6.28 6.42 6.47 6.60 7.3
## 2 87398900 5.68 6.36 6.5 6.57 6.84 7.4
## 3 87398950 5.71 6.28 6.46 6.46 6.68 7
## 4 87398980 5.42 6.10 6.36 6.39 6.6 7.2
## 5 87405500 5.64 6.34 6.5 6.49 6.7 7.01
## 6 87406900 5.6 6.4 6.48 6.51 6.77 7.3
## 7 87409900 5.59 6.46 6.6 6.57 6.76 7.2Time for this code chunk to run: 0.159032821655273
ggsave("pH.png",
units = c("px"),
width = 4500,
height = 2993,
plot = pH,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("pH_p1.png",
plot = pH_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("pH_p2.png",
plot = pH_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("pH_p3.png",
plot = pH_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("pH_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(pH_p1, pH_p2, pH_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time for
this code chunk to run: 6.0356719493866
8.0.8 Sólidos totais
(SolTot <- ggplot(plan_wide_19902020,
aes(CODIGO,
`Sólidos totais`))+
annotate("rect",
xmin = -Inf, xmax = Inf,
ymin = 500, ymax = Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Sólidos totais no período 1990-2020",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$`Sólidos totais`, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 1.33151006698608
(SolTot_p1 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000"),
aes(CODIGO,
`Sólidos totais`))+
annotate("rect",
xmin = -Inf, xmax = Inf,
ymin = 500, ymax = Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Sólidos totais no período 1990-2000",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$`Sólidos totais`, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.574917078018188
(SolTot_p2 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
`Sólidos totais`))+
annotate("rect",
xmin = -Inf, xmax = Inf,
ymin = 500, ymax = Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Sólidos totais no período 2000-2010",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$`Sólidos totais`, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.59086012840271
(SolTot_p3 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
`Sólidos totais`))+
annotate("rect",
xmin = -Inf, xmax = Inf,
ymin = 500, ymax = Inf,
alpha=1,
fill="#ac5079")+ #>pior classe
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Sólidos totais no período 2010-2020",
x="Estação",
y="")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$`Sólidos totais`, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.529263973236084
grid.arrange(SolTot_p1, SolTot_p2, SolTot_p3, ncol = 3)
Time
for this code chunk to run: 1.47361016273499
(sum_SolTot_p1 <- plan_wide_19902020 %>%
select(CODIGO, `Sólidos totais`, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(`Sólidos totais`,
na.rm = TRUE),
q1 =
quantile(`Sólidos totais`, 0.25,
na.rm = TRUE),
median =
median(`Sólidos totais`,
na.rm = TRUE),
mean =
mean(`Sólidos totais`,
na.rm= TRUE),
q3 =
quantile(`Sólidos totais`, 0.75,
na.rm = TRUE),
max =
max(`Sólidos totais`,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 46 84.5 95 122. 120 510
## 2 87398900 18 74.5 97 111. 122. 474
## 3 87398950 10 76.5 91 90.9 106. 155
## 4 87398980 48 63.5 81.5 104. 126. 337
## 5 87405500 70 101 121 133. 151 361
## 6 87406900 89 118 155 165. 210 279
## 7 87409900 20 99.5 122 128. 143 381(sum_SolTot_p2 <- plan_wide_19902020 %>%
select(CODIGO, `Sólidos totais`, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(`Sólidos totais`,
na.rm = TRUE),
q1 =
quantile(`Sólidos totais`, 0.25,
na.rm = TRUE),
median =
median(`Sólidos totais`,
na.rm = TRUE),
mean =
mean(`Sólidos totais`,
na.rm= TRUE),
q3 =
quantile(`Sólidos totais`, 0.75,
na.rm = TRUE),
max =
max(`Sólidos totais`,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 28 80 100 111. 123. 412
## 2 87398900 42 82 102. 128. 140. 489
## 3 87398950 46 94.2 108. 126. 127. 318
## 4 87398980 40 61 77 85.3 96 228
## 5 87405500 48 102 133 148. 170. 522
## 6 87406900 50 109 134. 154. 170. 670
## 7 87409900 56 112. 156 167. 190. 599(sum_SolTot_p3 <- plan_wide_19902020 %>%
select(CODIGO, `Sólidos totais`, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(`Sólidos totais`,
na.rm = TRUE),
q1 =
quantile(`Sólidos totais`, 0.25,
na.rm = TRUE),
median =
median(`Sólidos totais`,
na.rm = TRUE),
mean =
mean(`Sólidos totais`,
na.rm= TRUE),
q3 =
quantile(`Sólidos totais`, 0.75,
na.rm = TRUE),
max =
max(`Sólidos totais`,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 61 69 90 82.8 96 101
## 2 87398900 41 77 104 120. 127 308
## 3 87398950 45 93 101 109. 117 221
## 4 87398980 55 62.8 80 79.9 95 109
## 5 87405500 83 89.2 108. 124. 162. 195
## 6 87406900 50 106 117 135. 163 246
## 7 87409900 75 103 115 131. 145 251Time for this code chunk to run: 0.16404390335083
ggsave("SolTot.png",
units = c("px"),
width = 4500,
height = 2993,
plot = SolTot,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("SolTot_p1.png",
plot = SolTot_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("SolTot_p2.png",
plot = SolTot_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("SolTot_p3.png",
plot = SolTot_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("SolTot_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(SolTot_p1, SolTot_p2, SolTot_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.69993710517883
8.0.9 IQA
Time
for this code chunk to run: 1.02724814414978
Time
for this code chunk to run: 0.511719942092896
Time
for this code chunk to run: 0.478913068771362
Time
for this code chunk to run: 0.456027984619141
grid.arrange(iqa_p1, iqa_p2, iqa_p3, ncol = 3)
Time
for this code chunk to run: 1.30371594429016
(sum_IQA_p1 <- plan_wide_19902020 %>%
select(CODIGO, IQA, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(IQA,
na.rm = TRUE),
q1 =
quantile(IQA, 0.25,
na.rm = TRUE),
median =
median(IQA,
na.rm = TRUE),
mean =
mean(IQA,
na.rm= TRUE),
q3 =
quantile(IQA, 0.75,
na.rm = TRUE),
max =
max(IQA,
na.rm = TRUE),
n =
length(IQA)
)
)## # A tibble: 7 x 8
## CODIGO min q1 median mean q3 max n
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
## 1 87398500 27.0 35.7 40.9 40.7 46.2 52.2 101
## 2 87398900 27.8 37.9 42.9 43.0 48.0 58.5 101
## 3 87398950 32.8 36.8 41.4 43.2 48.6 61.9 68
## 4 87398980 29.2 35.8 40.4 40.3 44.8 51.9 30
## 5 87405500 24.8 34.9 41.2 40.3 46.9 57.6 97
## 6 87406900 24.7 31.3 37.8 37.4 44.4 49.0 32
## 7 87409900 23.6 31.9 37.1 38.8 46.2 55.4 65(sum_IQA_p2 <- plan_wide_19902020 %>%
select(CODIGO, IQA, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(IQA,
na.rm = TRUE),
q1 =
quantile(IQA, 0.25,
na.rm = TRUE),
median =
median(IQA,
na.rm = TRUE),
mean =
mean(IQA,
na.rm= TRUE),
q3 =
quantile(IQA, 0.75,
na.rm = TRUE),
max =
max(IQA,
na.rm = TRUE),
n =
length(IQA)
)
)## # A tibble: 7 x 8
## CODIGO min q1 median mean q3 max n
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
## 1 87398500 27.8 34.6 40.0 39.5 43.5 48.7 75
## 2 87398900 28.5 35.1 37.6 38.3 40.6 48.5 77
## 3 87398950 21.1 29.4 32.7 32.8 36.8 44.0 30
## 4 87398980 24.5 35.7 39.4 39.5 43.4 52.1 66
## 5 87405500 19.8 28.7 31.5 31.9 35.7 48.8 78
## 6 87406900 17.1 25.3 29.0 29.5 32.8 44.1 79
## 7 87409900 16.2 20.5 26.1 25.0 29.8 33.1 31(sum_IQA_p3 <- plan_wide_19902020 %>%
select(CODIGO, IQA, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
# ?as_factor(CODIGO) %>%
group_by(CODIGO) %>%
summarize(
min =
min(IQA,
na.rm = TRUE),
q1 =
quantile(IQA, 0.25,
na.rm = TRUE),
median =
median(IQA,
na.rm = TRUE),
mean =
mean(IQA,
na.rm= TRUE),
q3 =
quantile(IQA, 0.75,
na.rm = TRUE),
max =
max(IQA,
na.rm = TRUE),
n =
length(IQA),
NAs =
sum(is.na(IQA))
) %>%
mutate(
"%NA" = NAs/n*100
)
)## # A tibble: 7 x 10
## CODIGO min q1 median mean q3 max n NAs `%NA`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <int> <dbl>
## 1 87398500 40.2 42.5 45.4 44.2 45.5 47.2 34 29 85.3
## 2 87398900 34.1 38.6 41.2 40.2 42.9 44.4 36 32 88.9
## 3 87398950 36.7 39.5 42.4 41.5 44.4 44.6 35 31 88.6
## 4 87398980 40.0 40.0 40.0 40.0 40.0 40.0 28 27 96.4
## 5 87405500 30.8 31.6 32.5 32.5 33.3 34.1 33 31 93.9
## 6 87406900 22.9 24.4 25.9 25.3 26.5 27.2 35 32 91.4
## 7 87409900 24.1 25.1 27.3 26.9 28.2 29.7 37 32 86.5Time for this code chunk to run: 0.163351058959961
ggsave("iqa.png",
units = c("px"),
width = 4500,
height = 2993,
plot = iqa,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("iqa_p1.png",
plot = iqa_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("iqa_p2.png",
plot = iqa_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("iqa_p3.png",
plot = iqa_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("iqa_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(iqa_p1, iqa_p2, iqa_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.23654294013977
8.1 Testando coisas
8.1.1 Correlação
parametros_IQA %>%
select(-CODIGO) %>%
ggcorr(method = "complete.obs",
# "pearson",
# "pairwise",
name = "Correlação",
label = TRUE,
label_alpha = TRUE,
digits = 3,
low = "#3B9AB2",
mid = "#EEEEEE",
high = "#F21A00",
# palette = "RdYlBu",
layout.exp = 0,
legend.position = "left",
label_round = 3,
)
# Gráfico das correlações entre todos os parâmetros com significância
correl_IQA <- parametros_IQA %>%
select(-CODIGO) %>%
ggpairs(title = "Correlação entre parâmetros que compõem o IQA",
axisLabels = "show")Time for this code chunk to run: 0.548813104629517
8.1.2 Condutividade elétrica
(cond_elet <- ggplot(plan_wide_19902020,
aes(CODIGO,
Condutividade))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=500,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
facet_wrap(~periodo)+
labs(title = "Condutividade elétrica no período 1990-2020",
x="Estação",
y="µmhos/cm")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 1.38324618339539
(cond_elet_p1 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
Condutividade))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=500,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Condutividade elétrica no período 1990-2000",
x="Estação",
y="µmhos/cm")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.599011898040771
(cond_elet_p2 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010"),
aes(CODIGO,
Condutividade))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=500,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Condutividade elétrica no período 2000-2010",
x="Estação",
y="µmhos/cm")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.639420986175537
(cond_elet_p3 <- ggplot(plan_wide_19902020 %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020"),
aes(CODIGO,
Condutividade))+
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=500,
ymax=Inf,
alpha=1,
fill="#eb5661")+ #classe 4
annotate("rect",
xmin=-Inf,
xmax=Inf,
ymin=-Inf,
ymax=500,
alpha=1,
fill="#8dcdeb")+ #classe 1
stat_boxplot(geom = 'errorbar',
width=0.3,
position = position_dodge(width = 0.65))+
geom_boxplot(fill='#F8F8FF',
color="black",
outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
width= 0.7)+
labs(title = "Condutividade elétrica no período 2010-2020",
x="Estação",
y="µmhos/cm")+
scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
n.breaks = 8,
limits = c(0,
max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
labels = scales::number_format(accuracy = 1,
decimal.mark = ",",
big.mark = " "))+
ggbeeswarm::geom_quasirandom(
size = 1.2,
alpha = .25,
width = .07,
)+
scale_x_discrete(limits = c("87398500",
"87398980",
"87398900",
"87398950",
"87405500",
"87406900",
"87409900"),
labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
)+
geom_smooth(method = "lm",
se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
aes(group=1),
alpha=.5,
na.rm = TRUE,
size = 1)+
theme_grafs()
)
Time
for this code chunk to run: 0.513520956039429
grid.arrange(cond_elet_p1, cond_elet_p2, cond_elet_p3, ncol = 3)
Time
for this code chunk to run: 1.48326802253723
(sum_cond_elet_p1 <- plan_wide_19902020 %>%
select(CODIGO, Condutividade, ANO_COLETA) %>%
filter(ANO_COLETA>"1990" &
ANO_COLETA<="2000") %>%
group_by(CODIGO) %>%
summarize(
min =
min(Condutividade,
na.rm = TRUE),
q1 =
quantile(Condutividade, 0.25,
na.rm = TRUE),
median =
median(Condutividade,
na.rm = TRUE),
mean =
mean(Condutividade,
na.rm= TRUE),
q3 =
quantile(Condutividade, 0.75,
na.rm = TRUE),
max =
max(Condutividade,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 9.4 51.1 67 75.1 83.2 340
## 2 87398900 10 41.5 51 55.3 64.2 160
## 3 87398950 9 41.5 51.5 60.1 69.5 160
## 4 87398980 11.3 42.4 52.0 53.0 67.0 83.8
## 5 87405500 25 68.7 88.2 130. 170 560
## 6 87406900 52 88.4 133. 193. 256. 576
## 7 87409900 29 80 110. 134. 168. 460(sum_cond_elet_p2 <- plan_wide_19902020 %>%
select(CODIGO, Condutividade, ANO_COLETA) %>%
filter(ANO_COLETA>"2000" &
ANO_COLETA<="2010") %>%
group_by(CODIGO) %>%
summarize(
min =
min(Condutividade,
na.rm = TRUE),
q1 =
quantile(Condutividade, 0.25,
na.rm = TRUE),
median =
median(Condutividade,
na.rm = TRUE),
mean =
mean(Condutividade,
na.rm= TRUE),
q3 =
quantile(Condutividade, 0.75,
na.rm = TRUE),
max =
max(Condutividade,
na.rm = TRUE))
)## # A tibble: 7 x 7
## CODIGO min q1 median mean q3 max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 87398500 11.9 67.0 82.6 84.8 102. 164.
## 2 87398900 11 44.4 52.3 57.1 72.6 136.
## 3 87398950 39.8 58.4 76 82.3 98.3 160
## 4 87398980 9.4 42.4 49.7 51.5 62 114.
## 5 87405500 17 77.5 107 142. 171. 679
## 6 87406900 23.1 85.6 124. 164. 199. 619
## 7 87409900 56.1 114. 177 200. 242 454(sum_cond_elet_p3 <- plan_wide_19902020 %>%
select(CODIGO, Condutividade, ANO_COLETA) %>%
filter(ANO_COLETA>"2010" &
ANO_COLETA<="2020") %>%
group_by(CODIGO) %>%
summarize(
min =
min(Condutividade,
na.rm = TRUE),
q1 =
quantile(Condutividade, 0.25,
na.rm = TRUE),
median =
median(Condutividade,
na.rm = TRUE),
mean =
mean(Condutividade,
na.rm= TRUE),
q3 =
quantile(Condutividade, 0.75,
na.rm = TRUE),
max =
max(Condutividade,
na.rm = TRUE),
n =
length(Condutividade))
)## # A tibble: 7 x 8
## CODIGO min q1 median mean q3 max n
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
## 1 87398500 0.01 68.5 80.2 80.4 99.5 125. 34
## 2 87398900 39.7 53.4 58.3 61.1 65.5 103 36
## 3 87398950 40.9 64.7 70.1 76.1 82.5 195. 35
## 4 87398980 43.2 51.7 54.0 56.3 61.0 78.9 28
## 5 87405500 47 85.8 121. 146. 209. 286 33
## 6 87406900 62.7 95.9 142. 163. 216. 354. 35
## 7 87409900 65.7 121. 159. 179. 245. 498. 37# plan_wide_19902020 %>%
# select(CODIGO, IQA) %>%
# group_by(CODIGO) %>%
# summarize(
# min =
# min(IQA,
# na.rm = TRUE),
# q1 =
# quantile(IQA, 0.25,
# na.rm = TRUE),
# median =
# median(IQA,
# na.rm = TRUE),
# mean =
# mean(IQA,
# na.rm= TRUE),
# q3 =
# quantile(IQA, 0.75,
# na.rm = TRUE),
# max =
# max(IQA,
# na.rm = TRUE))Time for this code chunk to run: 0.178599834442139
ggsave("cond_elet.png",
units = c("px"),
width = 4500,
height = 2993,
plot = cond_elet,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("cond_elet_p1.png",
plot = cond_elet_p1,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("cond_elet_p2.png",
plot = cond_elet_p2,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("cond_elet_p3.png",
plot = cond_elet_p3,
path = "./graficos",
dpi = 300,
type = "cairo")
ggsave("cond_elet_3periodos.png",
units = c("px"),
width = 4500,
height = 2993,
plot = grid.arrange(cond_elet_p1, cond_elet_p2, cond_elet_p3, ncol = 3),
path = "./graficos",
dpi = 300,
type = "cairo")Time
for this code chunk to run: 5.34125995635986
---
title: "TCC"
author: "Leonardo Fernandes Wink"
date: "`r format(Sys.time(), '%d/%m/%Y')`"
output:
  html_document: 
    highlight: haddock
    keep_md: yes
    number_sections: yes
    theme: flatly
    toc: yes
    toc_float:
      collapsed: no
      smooth_scroll: no
    fig_width: 10
    fig_height: 6.66
    fig_caption: yes
    code_download: true
  pdf_document:
    toc: yes
  word_document: 
    toc: yes
    keep_md: yes
  github_document:
    html_preview: true
always_allow_html: yes
editor_options: 
  chunk_output_type: console
fig.align: center
---

```{r Rotina pra toda vez que abrir o documento, echo = FALSE}
# Abrir o GitHub Desktop
# Verificar se há pull pra ser feito
# Abrir o RStudio
```

# Brief explanation

Every boxplot means a monitoring point (Ponto de monitoramento (or PM) in portuguese). My goal here is to analyze the evolution between decades of each water quality parameter that compounds the Water Quality Index (WQI).

The river flows in the east-west direction as shown in the image below.

![](images/paste-7AD7027F.png)

The logic behind the sorting in the boxplots is because of 2 main reasons:

1.  The original monitoring point isn't easy to understand (8 digits, like 87409900)
2.  Changing the original nomenclature to PM1, PM2 (...) makes it easier to understand that the last point has water contributions of every other point upstream.

Some features that I want to add:
*  If the parameter is x, then use x's classes (with its own classes background color plotted)
*  Define the timescale, should act just like a filter

```{r p1 example}
# plan_wide_19902020 %>%
#   filter(ANO_COLETA > "1990" &
#          ANO_COLETA <= "2000")
```

# Anotações de coisas por fazer:

-   Descobrir como colocar as estações no sentido correto montante -\> jusante nos sumários

> 87398500, 87398980, 87398900, 87398950, 87405500, 87406900, 87409900

-   ~~Aprender a segmentar o meu dataset por períodos~~
-   aprender a criar uma nova coluna com a segmentação dos períodos
-   maybe use `~facet.grid`
-   aprender a colocar a legenda dentro do gráfico
    -   reduzir o tamanho da legenda
-   ~~corrigir os valores 0 de IQA pra NA~~
-   descobrir como conseguir a equação do lm
-   ~~aprender a pivotar o sumário~~ -\> meu sumário do google docs ta batendo direitinho com o do R
-   descobrir se há outros TCCs com disponibilização de códigos
-   `Namon` tá com com casa decimal `","` e `ptot` tá com `"."`
-   correlação forte entre condutividade e Namon/Ptot/DBO

| 1990-2000 | 2000-2010 | 2010-2020 |
|:---------:|:---------:|:---------:|
| 1990-2000 | 2000-2010 | 2010-2020 |

# Instalar os pacotes

```{r instalar pacotes}
# install.packages(tidyverse)
```

## acessar os pacotes

```{r Acessar os pacotes, message = FALSE, warning = TRUE}
# library(readr)
# library(rmarkdown)
# # library(qboxplot)
# library(readxl)
# library(pillar)
# library(dplyr)
# library(tidyverse)
# library(gapminder)
# library(knitr)
# library(kableExtra)
# library(ggpubr)
# library(gridExtra)
# library(modelsummary)
# library(gtsummary)
# library(GGally)
pacman::p_load(readr, rmarkdown, readxl,
               pillar, dplyr, tidyverse,
               gapminder, knitr, kableExtra,
               gridExtra, #modelsummary, 
               gtsummary, ggplot2,
               ggbeeswarm, GGally)
# pacman::p_load(tibbletime)
```

```{r cronometrando quanto tempo cada chunk leva}
knitr::knit_hooks$set(time_it = local({
   now <- NULL
   function(before, options) {
      if (before) {
         # record the current time before each chunk
         now <<- Sys.time()
      } else {
         # calculate the time difference after a chunk
         res <- difftime(Sys.time(), now)
         # return a character string to show the time
         paste("Time for this code chunk to run:", res)
      }
   }
}))

knitr::opts_chunk$set(time_it = TRUE)
```

```{r setup, include=FALSE}
# knitr::opts_chunk$set(echo = TRUE)
```

## importando a planilha

```{r Importando a planilha, echo = FALSE, message = TRUE, warning = FALSE}
plan_wide_19902020 <- read_delim("https://raw.githubusercontent.com/leonardofwink/TCC_gh/main/plan_wide_19902020.tsv",
                                 delim = "\t", 
                                 escape_double = FALSE,
                                 col_types = cols(
                                    Alcalinidade = col_double(),
                                    CODIGO = col_character(), 
                                    COORD_GEO_LAT_GRAU = col_double(),
                                    COORD_GEO_LONG_GRAU = col_double(),
                                    DATA_COLETA = col_date(format = "%d/%m/%Y"),
                                    Nitrato = col_double(), 
                                    Nitrito = col_double(),
                                    SDT = col_double(), 
                                    SST = col_double(),
                                    `Vazao` = col_double(), 
                                    `Vazao rio` = col_double()
                                 ),
                                 locale = locale(
                                    date_names = "pt", 
                                    decimal_mark = ",",
                                    grouping_mark = ""
                                 ),
                                 trim_ws = TRUE
)

# teste <- plan_wide_19902020 %>%
#   dplyr::filter(DATA_COLETA >= as.POSIXct("2010-01-01")) #this works
# 
# teste$DATA_COLETA <- as.POSIXct(teste$DATA_COLETA)
# 
# teste %>% 
#   dplyr::arrange(DATA_COLETA)
# teste %>% 
#   filter_time(time_formula = '2013-01-01' ~ '2020-12-31')
# 
# 
# typeof(teste$DATA_COLETA)
# 
#   as_tbl_time(plan_wide_19902020, index = DATA_COLETA)
# str(plan_wide_19902020$DATA_COLETA)
```

```{r Visualização da planilha importada, echo = FALSE}
paged_table(plan_wide_19902020,
            options = list(rows.print = 15,
                           cols.print = 10))
```

# data wrangling

```{r data wrangling}
# Como há dados faltantes, no cálculo entre o produto das colunas, ele acaba interpretando como se fosse zero, mas na verdade é NA
plan_wide_19902020 <- plan_wide_19902020 %>% 
   mutate(IQA = ifelse(IQA == 0, NA, IQA))

parametros_IQA <- plan_wide_19902020 %>%
  select(CODIGO,
         pH,
         DBO,
         `Escherichia coli`,
         `Nitrogênio amoniacal`,
         `Nitrogênio total`,
         `Fósforo total`,
         `Temperatura água`,
         Turbidez,
         `Sólidos totais`,
         `Oxigênio dissolvido`,
         Condutividade)

write.csv(parametros_IQA,
          "./parametros_IQA.csv",
          row.names = FALSE)
```

```{r Códigos Git, echo = FALSE}
# cd myrepo
# ls
# head README.md
# git status
# git add README.md
# git commit -m "A commit from my local computer"
# 
# cd .. # voltar pro diretório acima
# rm -rf myrepo/ #remover/apagar a pasta myrepo
```

```{r Aprendendo Git, echo = FALSE}
# slides da bia que ajudam mt
# https://beatrizmilz.github.io/slidesR/git_rstudio/11-2021-ENCE.html#20
# aprendendo a sincronizar usando esse guia -> 
# https://happygitwithr-com.translate.goog/push-pull-github.html?_x_tr_sl=auto&_x_tr_tl=pt&_x_tr_hl=pt-BR
# library(usethis)
# usethis::create_github_token() criar um código pra acesso e sincronização between R e github

# gitcreds::gitcreds_set() 
# 
# use_git_config(user.name = "leonardofwink",
#                user.email = "leonardofwink@gmail.com")
# usethis::gh_token_help()

# Como mostrar os dados de um arquivo via Git/GitHub
# git clone https://github.com/leonardofwink/myrepo.git
# cd myrepo #acessa a pasta myrepo
# ls #lista os arquivos da pasta 
# head README.md #mostra as primeiras observações do arquivo

# Como mostrar os dados de um arquivo via R
# head(C:/Users/Léo/myrepo/README.md)

# Adicionar uma linha ao README.md e verificar se o Git percebe a mudança
# echo "A line I wrote on my local computer" >> README.md
# git status
## C:\Users\Léo\myrepo>git status
## On branch main
## Your branch is up to date with 'origin/main'.
## 
## Changes not staged for commit:
##   (use "git add <file>..." to update what will be committed)
##   (use "git restore <file>..." to discard changes in working directory)
##         **modified:   README.md**
## 
## no changes added to commit (use "git add" and/or "git commit -a")
```

# setting theme

```{r setting theme}
theme_grafs <- function(bg = "white", 
                        coloracao_letra = "black") {
  theme(
    plot.title = 
      element_text(
        hjust = 0.5,
        color = coloracao_letra,
        size = 19),
    
    axis.title.x = 
      # element_text(
      # color = coloracao_letra,
      # size = 15,
      # angle = 0,),
      element_blank(),
    axis.title.y = element_text(
      color = coloracao_letra,
      size = 15,
      angle = 90),
    
    axis.text.x = element_text(
      color = coloracao_letra,
      size = 17),
    axis.text.y = element_text(
      color = coloracao_letra,
      size = 17,
      angle = 0),
    
    strip.background = element_rect(fill = bg,
                                    linetype = 1,
                                    size = 0.5,
                                    color = "black"),
    panel.background = element_rect(fill = bg),
    plot.background = element_rect(fill = bg),
    plot.margin = margin(l = 5, r = 10,
                         b = 5, t = 5)
  )
}
```

# setting different timescales

```{r setting periodos, echo = FALSE}
plan_wide_19902020 <- plan_wide_19902020 %>% 
  # select(CODIGO, ANO_COLETA) %>% 
  mutate(
    periodo = if_else(
      ANO_COLETA <= 2000, 
      "1990-2000",
      if_else(
        ANO_COLETA <= 2010,
        "2000-2010",
        "2010-2020"
      )
    )
  )
# summary(plan_wide_19902020$`Oxigênio dissolvido`)
```

# setting sumaries

```{r Sumários, echo = FALSE}
# plan_wide_19902020 %>%
#   as_tibble() %>% 
#   filter(ANO_COLETA > "1990" &
#            ANO_COLETA <= "2000") %>% 
#   select(colnames(parametros_IQA)) %>% 
#   group_by(CODIGO) %>% 
#   group_by(colnames(parametros_IQA)) %>% 
#   summarise_each(
#     funs( 
#       min = 
#         min(., 
#             na.rm = TRUE),
#       q1 = 
#         quantile(., 0.25, 
#                  na.rm = TRUE),
#       median = 
#         median(., 
#                na.rm = TRUE),
#       mean = 
#         mean(., 
#              na.rm= TRUE),
#       q3 = 
#         quantile(., 0.75, 
#                  na.rm = TRUE),
#       max = 
#         max(., 
#             na.rm = TRUE),
#       n = 
#         length(.)
#     )
#   ) %>% 
#   pivot_longer(
#        !CODIGO,
#        names_to = "parametro",
#        values_to = "valor"
#     ) %>% 
#     pivot_wider(names_from = CODIGO,
#                 values_from = valor) %>% 
#   group_by(parametro)



# p2 <- plan_wide_19902020 %>%
#   filter(ANO_COLETA > "2000" &
#          ANO_COLETA <= "2010")
# 
# p3 <- plan_wide_19902020 %>%
#   filter(ANO_COLETA > "2010" &
#          ANO_COLETA <= "2020")

# periodo = c(p1 <- plan_wide_19902020 %>% 
#   filter(ANO_COLETA > "1990" &
#            ANO_COLETA <= "2000"),
# 
# p2 <- plan_wide_19902020 %>%
#   filter(ANO_COLETA > "2000" &
#            ANO_COLETA <= "2010"),
# 
# p3 <- plan_wide_19902020 %>%
#   filter(ANO_COLETA > "2010" &
#            ANO_COLETA <= "2020"))

# sumario <- function(parametros = parametros, periodo){
#   plan_wide_19902020 %>%
#    select(CODIGO, ., ANO_COLETA) %>% 
#    # filter(ANO_COLETA>"1990" &
#    #          ANO_COLETA<="2000") %>% 
#    group_by(CODIGO) %>% 
#    summarize(
#      min = 
#        min(parametros, 
#            na.rm = TRUE),
#      q1 = 
#        quantile(parametros, 0.25, 
#                 na.rm = TRUE),
#      median = 
#        median(parametros, 
#               na.rm = TRUE),
#      mean = 
#        mean(parametros, 
#             na.rm= TRUE),
#      q3 = 
#        quantile(parametros, 0.75, 
#                 na.rm = TRUE),
#      max = 
#        max(parametros, 
#            na.rm = TRUE))
# }

# plan_wide_19902020 %>% 
#   sumario(parametros = DBO)

# sum_IQA_p1 <- plan_wide_19902020 %>%
#    select(CODIGO, IQA, ANO_COLETA) %>% 
#    filter(ANO_COLETA>"1990" &
#             ANO_COLETA<="2000") %>% 
#    group_by(CODIGO) %>% 
#    summarize(
#      min = 
#        min(IQA, 
#            na.rm = TRUE),
#      q1 = 
#        quantile(IQA, 0.25, 
#                 na.rm = TRUE),
#      median = 
#        median(IQA, 
#               na.rm = TRUE),
#      mean = 
#        mean(IQA, 
#             na.rm= TRUE),
#      q3 = 
#        quantile(IQA, 0.75, 
#                 na.rm = TRUE),
#      max = 
#        max(IQA, 
#            na.rm = TRUE))
```

# Parâmetros físico-químicos

### Oxigênio Dissolvido

```{r Gráfico OD facetted, echo = FALSE, warning=FALSE, message = FALSE, fig.cap="Oxigênio Dissolvido no período 1990-2020"}
(od <- plan_wide_19902020 %>% 
    ggplot(
      aes(
        x = CODIGO,
        y = `Oxigênio dissolvido`,
        # color = periodo,
        # fill = periodo
        )
    )+
    annotate("rect",
             xmin = -Inf, xmax = Inf,
             ymin = -Inf, ymax = 2,
             alpha = 1,
             fill = "#ac5079")+ #>pior classe
    annotate("rect",
             xmin = -Inf, xmax = Inf,
             ymin = 2, ymax = 4,
             alpha = 1,
             fill = "#eb5661")+ #classe 4
    annotate("rect",
             xmin = -Inf, xmax = Inf,
             ymin = 4, ymax = 5,
             alpha = 1,
             fill = "#fcf7ab")+ #classe 3
    annotate("rect",
             xmin = -Inf, xmax = Inf,
             ymin = 5, ymax = 6,
             alpha = 1,
             fill = "#70c18c")+ #classe 2
    annotate("rect",
             xmin = -Inf, xmax = Inf,
             ymin= 6, ymax = Inf,
             alpha = 1,
             fill = "#8dcdeb")+ #classe 1
    stat_boxplot(
      geom = 'errorbar',
      width = 0.3,
      position = position_dodge(width = 0.65)
    )+
    geom_boxplot(
      fill = '#F8F8FF',
      color = "black",
      outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
      width = 0.7
    )+
    facet_wrap(~periodo)+
    labs(
      title = "Oxigênio Dissolvido no período 1990-2020",
      x= NULL,
      y="mg/L"
    )+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(
      expand = expansion(mult = c(0,0)),
      n.breaks = 11,
      limits = c(-0.3,21)
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    # scale_fill_brewer(palette = "Set1")+
    scale_color_manual(name = "Período",
                       breaks = c("p1", "p2", "p3"),
                       values = c("black", "#303030", "#696969"),
                       labels = c("1990-2000", "2000-2010", "2010-2020")
    )+
    geom_smooth(
      method = "lm",
      se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
      aes(group = 1),
      alpha = .5,
      na.rm = TRUE,
      size = 1
    )+
  theme_grafs()
)
```


```{r Gráfico OD periodo 1, echo = FALSE, warning=FALSE, message = FALSE, fig.cap="Oxigênio Dissolvido no período 1990-2000"}
(od_p1 <- ggplot(plan_wide_19902020 %>% 
                    filter(ANO_COLETA > "1990" &
                              ANO_COLETA <= "2000"),
                 aes(CODIGO,
                     `Oxigênio dissolvido`)
)+
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = -Inf, ymax = 2,
            alpha = 1,
            fill = "#ac5079")+ #>pior classe
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 2, ymax = 4,
            alpha = 1,
            fill = "#eb5661")+ #classe 4
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 4, ymax = 5,
            alpha = 1,
            fill = "#fcf7ab")+ #classe 3
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 5, ymax = 6,
            alpha = 1,
            fill = "#70c18c")+ #classe 2
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin= 6, ymax = Inf,
            alpha = 1,
            fill = "#8dcdeb")+ #classe 1
   stat_boxplot(
      geom = 'errorbar',
      width = 0.3,
      position = position_dodge(width = 0.65)
   )+
   geom_boxplot(
      fill = '#F8F8FF',
      color = "black",
      outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
      width = 0.7
   )+
   labs(
      title = "Oxigênio Dissolvido no período 1990-2000",
      x="Estação",
      y="mg/L"
   )+
   ggbeeswarm::geom_quasirandom(
      size = 1.2,
      alpha = .25,
      width = .07,
   )+
   scale_y_continuous(
      expand = expansion(mult = c(0,0)),
      n.breaks = 11,
      limits = c(-1,21)
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(
      method = "lm",
      se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
      aes(group = 1),
      alpha = .5,
      na.rm = TRUE,
      size = 1
   )+
   theme_grafs()
)
```


```{r Gráfico OD periodo 2, echo = FALSE, warning=FALSE, message = FALSE}
(od_p2 <-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"2000" &
                             ANO_COLETA<="2010"),
                aes(CODIGO,
                    `Oxigênio dissolvido`))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=2,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=2,
             ymax=4,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=4,
             ymax=5,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=5,
             ymax=6,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=6,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Oxigênio Dissolvido no período 2000-2010",
         x="Estação",
         y=NULL)+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(
       expand = expansion(mult = c(0,0)),
       n.breaks = 11,
       limits = c(-1,21))+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(
       method = "lm",
       se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
       aes(group=1),
       alpha=.5,
       na.rm = TRUE,
       size = 1
    )+
    theme_grafs()
)
```


```{r Gráfico OD periodo 3, echo = FALSE, warning=FALSE, message = FALSE}
(od_p3 <-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"2010" &
                             ANO_COLETA<="2020") %>% 
                  group_by(CODIGO),
                aes(CODIGO,
                    `Oxigênio dissolvido`))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=2,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=2,
             ymax=4,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=4,
             ymax=5,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=5,
             ymax=6,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=6,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
   geom_boxplot(
     # aes(
     #   x = `Oxigênio dissolvido`,
     #   ymin = min(`Oxigênio dissolvido`),
     #   lower = quantile(`Oxigênio dissolvido`, 0.30, na.rm = TRUE),
     #   middle = median(`Oxigênio dissolvido`),
     #   upper = quantile(`Oxigênio dissolvido`, 0.80, na.rm = TRUE),
     #   ymax = max(`Oxigênio dissolvido`)
     # ),
     # stat = "identity",
     fill='#F8F8FF',
     color="black",
     outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
     width= 0.7
   )+
   labs(title = "Oxigênio Dissolvido no período 2010-2020",
        x=NULL,
        y=NULL)+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    scale_y_continuous(
       expand = expansion(mult = c(0,0)),
       n.breaks = 11,
       limits = c(-1,21))+
    geom_smooth(
       method = "lm",
       se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
       aes(group=1),
       alpha=.5,
       na.rm = TRUE,
       size = 1
    )+
    theme_grafs()
)
```

```{r Gráfico OD 3 periodos juntos, echo = TRUE, warning=FALSE, message = FALSE, fig.cap="Oxigênio Dissolvido no período 1990-2020"}
grid.arrange(od_p1, od_p2, od_p3, ncol = 3)
```

```{r Salvando OD, warning=FALSE, message = FALSE,}
ggsave("od.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = od,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("od_p1.png",
       plot = od_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("od_p2.png",
       plot = od_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("od_p3.png",
       plot = od_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("od_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(od_p1, od_p2, od_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

```{r Gráfico OD_chernobyl, echo = FALSE, warning=FALSE, message = FALSE}
# p1 <- function(plan_wide_19902020, ANO_COLETA) {
#   plan_wide_19902020 %>% 
#     filter(ANO_COLETA > "1990" &
#            ANO_COLETA <= "2000")
# }
# 
# 
# classes_od <- function(plan_wide_19902020, parametro, periodo){
#   ggplot(plan_wide_19902020 %>%
#            periodo),
#   aes(CODIGO,
#       parametro)
# }


# (od_chernobyl <- ggplot(plan_wide_19902020 %>%
#                           p1(ANO_COLETA > "1990" &
#                                ANO_COLETA <= "2000"),
#                         aes(CODIGO,
#                             `Oxigênio dissolvido`))+
#     annotate("rect",
#              xmin=-Inf,
#              xmax=Inf,
#              ymin=-Inf,
#              ymax=2,
#              alpha=1,
#              fill="#ac5079")+ #>pior classe
#     annotate("rect",
#              xmin=-Inf,
#              xmax=Inf,
#              ymin=2,
#              ymax=4,
#              alpha=1,
#              fill="#eb5661")+ #classe 4
#     annotate("rect",
#              xmin=-Inf,
#              xmax=Inf,
#              ymin=4,
#              ymax=5,
#              alpha=1,
#              fill="#fcf7ab")+ #classe 3
#     annotate("rect",
#              xmin=-Inf,
#              xmax=Inf,
#              ymin=5,
#              ymax=6,
#              alpha=1,
#              fill="#70c18c")+ #classe 2
#     annotate("rect",
#              xmin=-Inf,
#              xmax=Inf,
#              ymin=6,
#              ymax=Inf,
#              alpha=1,
#              fill="#8dcdeb")+ #classe 1
#     stat_boxplot(geom = 'errorbar',
#                  width=0.3,
#                  position = position_dodge(width = 0.65))+
#     geom_boxplot(fill='#F8F8FF',
#                  color="black",
#                  outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
#                  width= 0.7)+
#     labs(title = "Oxigênio Dissolvido no período 1990-2000",
#          x="Estação",
#          y="mg/L")+
#     # geom_jitter(width = .07,
#     #             alpha=.15,
#     #             size=1.,
#     #             color="black")+
#     ggbeeswarm::geom_quasirandom(
#       size = 1.2,
#       alpha = .25,
#       width = .07,
#     )+
#     scale_y_continuous(expand = expansion(mult = c(0,0)),
#                        n.breaks = 11,
#                        limits = c(-1,21))+
#     scale_x_discrete(limits = c("87398500",
#                                 "87398980",
#                                 "87398900",
#                                 "87398950",
#                                 "87405500",
#                                 "87406900",
#                                 "87409900"),
#                      labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
#     )+
#     geom_smooth(method = "lm",
#                 se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
#                 aes(group=1),
#                 alpha=.5,
#                 na.rm = TRUE,
#                 size = 1)+
#     # geom_line(
#     #   aes(color="red"),
#     #   alpha=.0)+
#     # scale_color_manual("Legenda",
#     #                    guide="legend",
#     #                    values = c("Classe 1"="#8dcdeb",
#     #                               "Classe 2"="#70c18c",
#     #                               "Classe 3"="#fcf7ab",
#     #                               "Classe 4"="#eb5661",
#     #                               "Pior Classe"="#ac5079"))+
#     # guides(color=guide_legend(override.aes = list(linetype=c(1,1,1,1,1),
#   #                                               lwd=c(2,2,2,2,2),
#   #                                               shape=c(NA,NA,NA,NA,NA),
#   #                                               alpha=1)))+
#   theme(
#     plot.title = element_text(size = 19),
#     axis.title.y = element_text(size = 15),
#     axis.text.y = element_text(size = 17),
#     axis.text.x = element_text(size = 17),
#   )
# )
```

```{r Gráfico IQA OD periodo1, echo = FALSE, message=FALSE, warning=FALSE}
(iqaod_p1 <-ggplot(plan_wide_19902020 %>% 
                      filter(ANO_COLETA > "1990" &
                                ANO_COLETA <= "2000"),
                   aes(CODIGO,
                       IQA_OD, na.rm = TRUE))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=19,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=19,
             ymax=36,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=36,
             ymax=51,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=51,
             ymax=79,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=79,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65),
                 na.rm = TRUE)+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7,
                 na.rm = TRUE)+
    labs(title = "Variação do IQA para o parâmetro Oxigênio Dissolvido 1990-2000",
         x="Estação",
         y="")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    scale_y_continuous(expand = expansion(mult = c(0,0)),
                       n.breaks = 6,
                       limits = c(-1,101))+
    geom_smooth(
       method = "lm",
       se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
       aes(group=1),
       alpha=.5,
       na.rm = TRUE,
       size = 1
    )+
    theme_grafs()
)
```

```{r Gráfico IQA OD periodo2, echo = FALSE, warning= FALSE, message = FALSE}
(iqaod_p2 <-ggplot(plan_wide_19902020 %>% 
                      filter(ANO_COLETA > "2000" &
                                ANO_COLETA <= "2010"),
                   aes(CODIGO,
                       IQA_OD, na.rm = TRUE))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=19,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=19,
             ymax=36,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=36,
             ymax=51,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=51,
             ymax=79,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=79,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65),
                 na.rm = TRUE)+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7,
                 na.rm = TRUE)+
    labs(title = "Variação do IQA para o parâmetro Oxigênio Dissolvido 2000-2010",
         x="Estação",
         y="")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(expand = expansion(mult = c(0,0)),
                       n.breaks = 6,
                       limits = c(-1,101))+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(
       method = "lm",
       se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
       aes(group=1),
       alpha=.5,
       na.rm = TRUE,
       size = 1
    )+
    theme_grafs()
)

```

```{r Gráfico IQA OD periodo3, echo = FALSE, warning=FALSE, message = FALSE}
(iqaod_p3 <-ggplot(plan_wide_19902020 %>% 
                      filter(ANO_COLETA > "2010" &
                                ANO_COLETA <= "2020"),
                   aes(CODIGO,
                       IQA_OD, na.rm = TRUE))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=19,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=19,
             ymax=36,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=36,
             ymax=51,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=51,
             ymax=79,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=79,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65),
                 na.rm = TRUE)+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7,
                 na.rm = TRUE)+
    labs(title = "Variação do IQA para o parâmetro Oxigênio Dissolvido 2010-2020",
         x="Estação",
         y="")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(expand = expansion(mult = c(0,0)),
                       n.breaks = 6,
                       limits = c(-1,101))+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(
       method = "lm",
       se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
       aes(group=1),
       alpha=.5,
       na.rm = TRUE,
       size = 1
    )+
    theme_grafs()
)
```

```{r Gráfico OD_IQA 6 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(iqaod_p1, iqaod_p2, iqaod_p3, ncol = 3)
```

```{r Sumário OD, echo = FALSE, warning=FALSE, message = FALSE,}
(sum_od_p1 <- plan_wide_19902020 %>%
    select(CODIGO, `Oxigênio dissolvido`, ANO_COLETA) %>% 
    filter(ANO_COLETA>"1990" &
              ANO_COLETA<="2000") %>% 
    group_by(CODIGO) %>% 
    summarize(
       min = 
          min(`Oxigênio dissolvido`, na.rm = TRUE),
       q1 = 
          quantile(`Oxigênio dissolvido`, 0.25, na.rm = TRUE),
       median = 
          median(`Oxigênio dissolvido`, na.rm = TRUE),
       mean = 
          mean(`Oxigênio dissolvido`, na.rm= TRUE),
       q3 = 
          quantile(`Oxigênio dissolvido`, 0.75, na.rm = TRUE),
       max = 
          max(`Oxigênio dissolvido`, na.rm = TRUE),
       n = 
          length(`Oxigênio dissolvido`)
    ) %>% 
    pivot_longer(
       !CODIGO,
       names_to = "par",
       values_to = "valor"
    ) %>% 
    pivot_wider(names_from = CODIGO,
                values_from = valor)
)

(sum_od_p2 <- plan_wide_19902020 %>%
      select(CODIGO, `Oxigênio dissolvido`, ANO_COLETA) %>% 
      filter(ANO_COLETA>"2000" &
                ANO_COLETA<="2010") %>% 
      group_by(CODIGO) %>% 
      summarize(
         min = 
            min(`Oxigênio dissolvido`, na.rm = TRUE),
         q1 = 
            quantile(`Oxigênio dissolvido`, 0.25, na.rm = TRUE),
         median = 
            median(`Oxigênio dissolvido`, na.rm = TRUE),
         mean = 
            mean(`Oxigênio dissolvido`, na.rm= TRUE),
         q3 = 
            quantile(`Oxigênio dissolvido`, 0.75, na.rm = TRUE),
         max = 
            max(`Oxigênio dissolvido`, na.rm = TRUE)
      )
)

(sum_od_p3 <- plan_wide_19902020 %>%
      select(CODIGO, `Oxigênio dissolvido`, ANO_COLETA) %>% 
      filter(ANO_COLETA>"2010" &
                ANO_COLETA<="2020") %>% 
      group_by(CODIGO) %>% 
      summarize(
         min = 
            min(`Oxigênio dissolvido`, na.rm = TRUE),
         q1 = 
            quantile(`Oxigênio dissolvido`, 0.25, na.rm = TRUE),
         median = 
            median(`Oxigênio dissolvido`, na.rm = TRUE),
         mean = 
            mean(`Oxigênio dissolvido`, na.rm= TRUE),
         q3 = 
            quantile(`Oxigênio dissolvido`, 0.75, na.rm = TRUE),
         max = 
            max(`Oxigênio dissolvido`, na.rm = TRUE)
      )
)

#   pivot_wider(id_cols = CODIGO,
#               names_from = CODIGO,
#               values_from = `Oxigênio dissolvido`)
# 
# 
#   group_by(CODIGO) %>%
#   get_summary_stats(type = "common") %>%
#   pivot_wider(id_cols = variable,
#               names_from = CODIGO,
#               values_from = variable$`Oxigênio dissolvido`)
# 
# # install.packages("ggpubr")
# # library(ggpubr)
```


### Demanda Bioquímica de Oxigênio

```{r Gráfico DBO facetted}
(dbo <- ggplot(plan_wide_19902020,
               aes(x = CODIGO,
                   y = DBO))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=10,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=5,
            ymax=10,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=3,
            ymax=5,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=3,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
   labs(title = "Demanda Bioquímica de Oxigênio no período 1990-2020",
        x="Estação",
        y="mg/L")+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                      n.breaks = 8,
                      limits = c(1,100),
                      trans = "log10")+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico DBO período1, echo = FALSE, warning = FALSE, message = FALSE}
(dbo_p1<-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"1990" &
                             ANO_COLETA<="2000"),
                aes(CODIGO,
                    DBO))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=10,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=5,
             ymax=10,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=3,
             ymax=5,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=3,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Demanda Bioquímica de Oxigênio no período 1990-2000",
         x="Estação",
         y="mg/L")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                       n.breaks = 8,
                       limits = c(1,100),
                       trans = "log10")+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico DBO período2, echo = FALSE, warning = FALSE, message = FALSE}
(dbo_p2<-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"2000" &
                             ANO_COLETA<="2010"),
                aes(CODIGO,
                    DBO))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=10,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=5,
             ymax=10,
             alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=3,
            ymax=5,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=3,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Demanda Bioquímica de Oxigênio no período 2000-2010",
        x="Estação",
        y="mg/L")+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                       n.breaks = 8,
                       limits = c(1,100),
                       trans = "log10")+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico DBO período3, echo = FALSE, warning = FALSE, message = FALSE}
(dbo_p3<-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"2010" &
                             ANO_COLETA<="2020"),
                aes(CODIGO,
                    DBO, na.rm=TRUE))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=10,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=5,
             ymax=10,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=3,
             ymax=5,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=3,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Demanda Bioquímica de Oxigênio no período 2010-2020",
         x="Estação",
         y="mg/L")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                       n.breaks = 8,
                       limits = c(1,100),
                       trans = "log10")+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
        geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico IQA DBO periodo1, echo = FALSE, warning = FALSE, message = FALSE}
(iqa_dbo1<-ggplot(plan_wide_19902020 %>% 
                    filter(ANO_COLETA>"1990" &
                             ANO_COLETA<="2000"),
                  aes(CODIGO,
                      IQA_DBO))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=19,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=19,
            ymax=36,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=36,
            ymax=51,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=51,
            ymax=79,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=79,
            ymax=Inf,
            alpha=1,
            fill="#8dcdeb")+ #classe 1))
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65),
                na.rm = TRUE)+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Variação do IQA para o parâmetro DBO 1990-2020",
        x="Estação",
        y="mg/L")+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_y_continuous(expand = expansion(mult = c(0,0)),
                      n.breaks = 6,
                      limits = c(-1,101))+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico IQA DBO periodo2, echo = FALSE, warning = FALSE, message = FALSE}
(iqa_dbo2<-ggplot(plan_wide_19902020%>% 
                     filter(ANO_COLETA>"2000" &
                               ANO_COLETA<="2010"),
                  aes(CODIGO,
                      IQA_DBO))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=19,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=19,
             ymax=36,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=36,
             ymax=51,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=51,
             ymax=79,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=79,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1))
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65),
                 na.rm = TRUE)+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Variação do IQA para o parâmetro DBO 2000-2010",
         x="Estação",
         y="mg/L")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(expand = expansion(mult = c(0,0)),
                       n.breaks = 6,
                       limits = c(-1,101))+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico IQA DBO periodo3, echo = FALSE, warning = FALSE, message = FALSE}
(iqa_dbo3<-ggplot(plan_wide_19902020%>% 
                     filter(ANO_COLETA>"2010" &
                               ANO_COLETA<="2020"),
                  aes(CODIGO,
                      IQA_DBO))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=19,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=19,
             ymax=36,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=36,
             ymax=51,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=51,
             ymax=79,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=79,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1))
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65),
                 na.rm = TRUE)+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Variação do IQA para o parâmetro DBO 2010-2020",
         x="Estação",
         y="mg/L")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(expand = expansion(mult = c(0,0)),
                       n.breaks = 6,
                       limits = c(-1,101))+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
        geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico DBO 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(dbo_p1, dbo_p2, dbo_p3, ncol = 3)
```

```{r Sumário DBO, warning=FALSE, message = FALSE,}
(sum_dbo_p1 <- plan_wide_19902020 %>%
   select(CODIGO, DBO, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(DBO, 
           na.rm = TRUE),
     q1 = 
       quantile(DBO, 0.25, 
                na.rm = TRUE),
     median = 
       median(DBO, 
              na.rm = TRUE),
     mean = 
       mean(DBO, 
            na.rm= TRUE),
     q3 = 
       quantile(DBO, 0.75, 
                na.rm = TRUE),
     max = 
       max(DBO, 
           na.rm = TRUE))
)

(sum_dbo_p2 <- plan_wide_19902020 %>%
    select(CODIGO, DBO, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(DBO, 
            na.rm = TRUE),
      q1 = 
        quantile(DBO, 0.25, 
                 na.rm = TRUE),
      median = 
        median(DBO, 
               na.rm = TRUE),
      mean = 
        mean(DBO, 
             na.rm= TRUE),
      q3 = 
        quantile(DBO, 0.75, 
                 na.rm = TRUE),
      max = 
        max(DBO, 
            na.rm = TRUE))
)

(sum_dbo_p3 <- plan_wide_19902020 %>%
    select(CODIGO, DBO, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(DBO, 
            na.rm = TRUE),
      q1 = 
        quantile(DBO, 0.25, 
                 na.rm = TRUE),
      median = 
        median(DBO, 
               na.rm = TRUE),
      mean = 
        mean(DBO, 
             na.rm= TRUE),
      q3 = 
        quantile(DBO, 0.75, 
                 na.rm = TRUE),
      max = 
        max(DBO, 
            na.rm = TRUE))
)
```

```{r Salvando DBO, warning=FALSE, message = FALSE,}
ggsave("dbo.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = dbo,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("dbo_p1.png",
       plot = dbo_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("dbo_p2.png",
       plot = dbo_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("dbo_p3.png",
       plot = dbo_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("dbo_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(dbo_p1, dbo_p2, dbo_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### Fósforo total

```{r Gráfico fósforo total facetted}
(ptot <- ggplot(plan_wide_19902020,
                aes(CODIGO,
                    `Fósforo total`))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0.15,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0.1,
            ymax=0.15,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=0.1,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
  facet_wrap(~periodo)+
    labs(title = "Fósforo total no período 1990-2020",
         x="Estação",
         y="mg/L")+
   scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                      n.breaks = 8,
                      limits = c(min(plan_wide_19902020$`Fósforo total`, na.rm = TRUE),
                                 max(plan_wide_19902020$`Fósforo total`), na.rm = TRUE),
                      trans = "log10")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico Fósforo total periodo1, warning = FALSE, message = FALSE}
(ptot_p1<-ggplot(plan_wide_19902020%>% 
                   filter(ANO_COLETA>"1990" &
                             ANO_COLETA<="2000"),
                 aes(CODIGO,
                     `Fósforo total`))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0.15,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0.1,
             ymax=0.15,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=0.1,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Fósforo total no período 1990-2000",
         x="Estação",
         y="mg/L")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                       n.breaks = 8,
                       limits = c(min(plan_wide_19902020$`Fósforo total`, na.rm = TRUE),
                                  max(plan_wide_19902020$`Fósforo total`), na.rm = TRUE),
                       trans = "log10")+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)

```

```{r Gráfico Fósforo total periodo2, warning = FALSE, message = FALSE}
(ptot_p2 <- ggplot(plan_wide_19902020%>% 
                      filter(ANO_COLETA>"2000" &
                                ANO_COLETA<="2010"),
                   aes(CODIGO,
                       `Fósforo total`))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0.15,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0.1,
             ymax=0.15,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=0.1,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Fósforo total no período 2000-2010",
         x="Estação",
         y="mg/L")+
   scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                      n.breaks = 8,
                      limits = c(min(plan_wide_19902020$`Fósforo total`, na.rm = TRUE),
                                 max(plan_wide_19902020$`Fósforo total`), na.rm = TRUE),
                      trans = "log10")+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)

```

```{r Gráfico Fósforo total periodo3, warning = FALSE, message = FALSE}
(ptot_p3 <- ggplot(plan_wide_19902020%>% 
                      filter(ANO_COLETA>"2010" &
                                ANO_COLETA<="2020"),
                   aes(CODIGO,
                       `Fósforo total`))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0.15,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0.1,
             ymax=0.15,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=0.1,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Fósforo total no período 2010-2020",
         x="Estação",
         y="mg/L")+
    scale_y_continuous(expand = expansion(mult = c(0.03,0.03)),
                       n.breaks = 8,
                       limits = c(min(plan_wide_19902020$`Fósforo total`, na.rm = TRUE),
                                  max(plan_wide_19902020$`Fósforo total`), na.rm = TRUE),
                       trans = "log10")+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)

```

```{r Gráfico Ptot 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(ptot_p1, ptot_p2, ptot_p3, ncol = 3)
```

```{r Sumário Fósforo total, warning=FALSE, message = FALSE,}
(sum_ptot_p1 <- plan_wide_19902020 %>%
    select(CODIGO, `Fósforo total`, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(`Fósforo total`, na.rm = TRUE),
     q1 = 
       quantile(`Fósforo total`, 0.25, na.rm = TRUE),
     median = 
       median(`Fósforo total`, na.rm = TRUE),
     mean = 
       mean(`Fósforo total`, na.rm= TRUE),
     q3 = 
       quantile(`Fósforo total`, 0.75, na.rm = TRUE),
     max = 
       max(`Fósforo total`, na.rm = TRUE)))

(sum_ptot_p2 <- plan_wide_19902020 %>%
    select(CODIGO, `Fósforo total`, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(`Fósforo total`, na.rm = TRUE),
      q1 = 
        quantile(`Fósforo total`, 0.25, na.rm = TRUE),
      median = 
        median(`Fósforo total`, na.rm = TRUE),
      mean = 
        mean(`Fósforo total`, na.rm= TRUE),
      q3 = 
        quantile(`Fósforo total`, 0.75, na.rm = TRUE),
      max = 
        max(`Fósforo total`, na.rm = TRUE)))

(sum_ptot_p3 <- plan_wide_19902020 %>%
    select(CODIGO, `Fósforo total`, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(`Fósforo total`, na.rm = TRUE),
      q1 = 
        quantile(`Fósforo total`, 0.25, na.rm = TRUE),
      median = 
        median(`Fósforo total`, na.rm = TRUE),
      mean = 
        mean(`Fósforo total`, na.rm= TRUE),
      q3 = 
        quantile(`Fósforo total`, 0.75, na.rm = TRUE),
      max = 
        max(`Fósforo total`, na.rm = TRUE)))

```

```{r Salvando Ptot, warning=FALSE, message = FALSE,}
ggsave("ptot.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = ptot,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ptot_p1.png",
       plot = ptot_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ptot_p2.png",
       plot = ptot_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ptot_p3.png",
       plot = ptot_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ptot_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(ptot_p1, ptot_p2, ptot_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### Escherichia coli

```{r Gráfico Ecoli facetted, warning = FALSE, message = FALSE}
(ecoli <- ggplot(plan_wide_19902020,
                 aes(CODIGO,
                     `Escherichia coli`))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=3200,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=800,
            ymax=3200,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=160,
            ymax=800,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=160,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
   labs(title = "Escherichia coli no período 1990-2020",
        x="Estação",
        y="NMP/100mL")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                      n.breaks = 9,
                      limits = c(min(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE),
                                 max(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Ecoli periodo1, warning = FALSE, message = FALSE}
(ecoli_p1 <- ggplot(plan_wide_19902020 %>% 
                       filter(ANO_COLETA>"1990" &
                                 ANO_COLETA<="2000"),
                    aes(CODIGO,
                        `Escherichia coli`))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=3200,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=800,
             ymax=3200,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=160,
             ymax=800,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=160,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Escherichia coli no período 1990-2000",
         x="Estação",
         y="NMP/100mL")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                      n.breaks = 9,
                      limits = c(min(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE),
                                 max(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico Ecoli periodo2, warning = FALSE, message = FALSE}
(ecoli_p2 <- ggplot(plan_wide_19902020 %>% 
                       filter(ANO_COLETA>"2000" &
                                 ANO_COLETA<="2010"),
                    aes(CODIGO,
                        `Escherichia coli`))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=3200,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=800,
             ymax=3200,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=160,
             ymax=800,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=160,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Escherichia coli no período 2000-2010",
         x="Estação",
         y="NMP/100mL")+
    scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                       n.breaks = 9,
                       limits = c(min(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE),
                                  max(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE)),
                       trans = "log10",
                       labels = scales::number_format(accuracy = 1,
                                                      decimal.mark = ",",
                                                      big.mark = " "))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico Ecoli periodo3, warning = FALSE, message = FALSE}
(ecoli_p3 <- ggplot(plan_wide_19902020 %>% 
                       filter(ANO_COLETA>"2010" &
                                 ANO_COLETA<="2020"),
                    aes(CODIGO,
                        `Escherichia coli`))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=3200,
             ymax=Inf,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=800,
             ymax=3200,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=160,
             ymax=800,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=160,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Escherichia coli no período 2010-2020",
         x="Estação",
         y="NMP/100mL")+
    scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                       n.breaks = 9,
                       limits = c(min(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE),
                                  max(plan_wide_19902020$`Escherichia coli`, na.rm = TRUE)),
                       trans = "log10",
                       labels = scales::number_format(accuracy = 1,
                                                      decimal.mark = ",",
                                                      big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico ecoli 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(ecoli_p1, ecoli_p2, ecoli_p3, ncol = 3)
```

```{r Sumário Ecoli, warning=FALSE, message = FALSE,}
(sum_ecoli_p1 <- plan_wide_19902020 %>%
    select(CODIGO, `Escherichia coli`, ANO_COLETA) %>% 
    filter(ANO_COLETA>"1990" &
              ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(`Escherichia coli`, 
           na.rm = TRUE),
     q1 = 
       quantile(`Escherichia coli`, 0.25, 
                na.rm = TRUE),
     median = 
       median(`Escherichia coli`, 
              na.rm = TRUE),
     mean = 
       mean(`Escherichia coli`, 
            na.rm= TRUE),
     q3 = 
       quantile(`Escherichia coli`, 0.75, 
                na.rm = TRUE),
     max = 
       max(`Escherichia coli`, 
           na.rm = TRUE))
)

(sum_ecoli_p2 <- plan_wide_19902020 %>%
    select(CODIGO, `Escherichia coli`, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(`Escherichia coli`, 
            na.rm = TRUE),
      q1 = 
        quantile(`Escherichia coli`, 0.25, 
                 na.rm = TRUE),
      median = 
        median(`Escherichia coli`, 
               na.rm = TRUE),
      mean = 
        mean(`Escherichia coli`, 
             na.rm= TRUE),
      q3 = 
        quantile(`Escherichia coli`, 0.75, 
                 na.rm = TRUE),
      max = 
        max(`Escherichia coli`, 
            na.rm = TRUE))
)

(sum_ecoli_p3 <- plan_wide_19902020 %>%
    select(CODIGO, `Escherichia coli`, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(`Escherichia coli`, 
            na.rm = TRUE),
      q1 = 
        quantile(`Escherichia coli`, 0.25, 
                 na.rm = TRUE),
      median = 
        median(`Escherichia coli`, 
               na.rm = TRUE),
      mean = 
        mean(`Escherichia coli`, 
             na.rm= TRUE),
      q3 = 
        quantile(`Escherichia coli`, 0.75, 
                 na.rm = TRUE),
      max = 
        max(`Escherichia coli`, 
            na.rm = TRUE))
)
```

```{r Salvando ecoli, warning=FALSE, message = FALSE,}
ggsave("ecoli.png",
       plot = ecoli,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ecoli_p1.png",
       plot = ecoli_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ecoli_p2.png",
       plot = ecoli_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ecoli_p3.png",
       plot = ecoli_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("ecoli_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(ecoli_p1, ecoli_p2, ecoli_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### Nitrogênio amoniacal

```{r Gráfico Nitrogênio total facetted, warning = FALSE, message = FALSE}
(namon <- ggplot(plan_wide_19902020,
                 aes(CODIGO,
                     `Nitrogênio total`))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=13.3,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=3.7,
            ymax=13.3,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=3.7,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
   labs(title = "Nitrogênio amoniacal no período 1990-2020",
        x="Estação",
        y="mg/L")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 9,
                      limits = c(min(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE),
                                 max(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = .001,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Nitrogênio total periodo1, warning = FALSE, message = FALSE}
(namon_p1 <- ggplot(plan_wide_19902020 %>% 
                      filter(ANO_COLETA>"1990" &
                               ANO_COLETA<="2000"),
                    aes(CODIGO,
                        `Nitrogênio total`))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=13.3,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=3.7,
             ymax=13.3,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=0,
             ymax=3.7,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
   labs(title = "Nitrogênio amoniacal no período 1990-2000",
        x="Estação",
        y="mg/L")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 9,
                      limits = c(min(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE),
                                 max(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = .001,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Nitrogênio total periodo2, warning = FALSE, message = FALSE}
(namon_p2 <- ggplot(plan_wide_19902020 %>% 
                      filter(ANO_COLETA>"2000" &
                               ANO_COLETA<="2010"),
                    aes(CODIGO,
                        `Nitrogênio total`))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=13.3,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=3.7,
            ymax=13.3,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=3.7,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Nitrogênio amoniacal no período 2000-2010",
        x="Estação",
        y="mg/L")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 9,
                      limits = c(min(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE),
                                 max(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = .001,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Nitrogênio total periodo3, warning = FALSE, message = FALSE}
(namon_p3 <- ggplot(plan_wide_19902020 %>% 
                       filter(ANO_COLETA>"2010" &
                                 ANO_COLETA<="2020"),
                    aes(CODIGO,
                        `Nitrogênio total`))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=13.3,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=3.7,
            ymax=13.3,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=3.7,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Nitrogênio amoniacal no período 2010-2020",
        x="Estação",
        y="mg/L")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 9,
                      limits = c(min(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE),
                                 max(plan_wide_19902020$`Nitrogênio total`, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = .001,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Namon 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(namon_p1, namon_p2, namon_p3, ncol = 3)
```

```{r Sumário Nitrogênio total, warning=FALSE, message = FALSE,}
(sum_namon_p1 <- plan_wide_19902020 %>%
   select(CODIGO, `Nitrogênio total`, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(`Nitrogênio total`, 
           na.rm = TRUE),
     q1 = 
       quantile(`Nitrogênio total`, 0.25, 
                na.rm = TRUE),
     median = 
       median(`Nitrogênio total`, 
              na.rm = TRUE),
     mean = 
       mean(`Nitrogênio total`, 
            na.rm= TRUE),
     q3 = 
       quantile(`Nitrogênio total`, 0.75, 
                na.rm = TRUE),
     max = 
       max(`Nitrogênio total`, 
           na.rm = TRUE),
      n = 
       length(`Nitrogênio total`)
   )
)

(sum_namon_p2 <- plan_wide_19902020 %>%
    select(CODIGO, `Nitrogênio total`, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(`Nitrogênio total`, 
            na.rm = TRUE),
      q1 = 
        quantile(`Nitrogênio total`, 0.25, 
                 na.rm = TRUE),
      median = 
        median(`Nitrogênio total`, 
               na.rm = TRUE),
      mean = 
        mean(`Nitrogênio total`, 
             na.rm= TRUE),
      q3 = 
        quantile(`Nitrogênio total`, 0.75, 
                 na.rm = TRUE),
      max = 
        max(`Nitrogênio total`, 
            na.rm = TRUE))
)

(sum_namon_p3 <- plan_wide_19902020 %>%
    select(CODIGO, `Nitrogênio total`, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(`Nitrogênio total`, 
            na.rm = TRUE),
      q1 = 
        quantile(`Nitrogênio total`, 0.25, 
                 na.rm = TRUE),
      median = 
        median(`Nitrogênio total`, 
               na.rm = TRUE),
      mean = 
        mean(`Nitrogênio total`, 
             na.rm= TRUE),
      q3 = 
        quantile(`Nitrogênio total`, 0.75, 
                 na.rm = TRUE),
      max = 
        max(`Nitrogênio total`, 
            na.rm = TRUE))
)
```

```{r Salvando namon, warning=FALSE, message = FALSE,}
ggsave("namon.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = namon,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("namon_p1.png",
       plot = namon_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("namon_p2.png",
       plot = namon_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("namon_p3.png",
       plot = namon_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("namon_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(namon_p1, namon_p2, namon_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### Turbidez

```{r Gráfico Turbidez facetted, warning = FALSE, message = FALSE}
(turb <- ggplot(plan_wide_19902020,
                   aes(CODIGO,
                       Turbidez))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=100,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=40,
            ymax=100,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=40,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
   labs(title = "Turbidez no período 1990-2020",
        x="Estação",
        y="UNT")+
   scale_y_continuous(expand = expansion(mult = c(0.05, 0.05)),
                      n.breaks = 16,
                      limits = c(min(plan_wide_19902020$Turbidez, na.rm = TRUE),
                                 500
                                 # max(plan_wide_19902020$Turbidez, na.rm = TRUE)
                                 ),
                      # trans = "log10",
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)

plan_wide_19902020 %>% 
  filter(ANO_COLETA>"1990" &
           ANO_COLETA<="2020") %>% 
  select(CODIGO, Turbidez, DATA_COLETA) %>% 
  group_by(CODIGO) %>% 
  ggplot(aes(x = DATA_COLETA,
             y = Turbidez,
             # color = Turbidez
             ))+
  geom_point(na.rm = TRUE)+
  geom_smooth(
    method = "lm",
    # formula = y ~ poly(x, 2),
    span = 0.2,
    se = TRUE, #se deixar TRUE gera o intervalo de confiança de 95%
    aes(group = 1),
    alpha =.5,
    na.rm = TRUE,
    size = 0.3,
    fullrange = TRUE,
    show.legend = TRUE
  )+
  stat_smooth(
    geom = "smooth",
    # span = 0.2,
    se = FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
    # aes(group = 1),
    # alpha =.5,
    na.rm = TRUE,
    # size = 0.3,
    fullrange = TRUE,
    show.legend = TRUE
  )+
  facet_wrap(
    ~CODIGO,
    nrow = 4,
  )+
  # scale_x_continuous(expand = expansion(mult = c(0.05, 0.03)))+
  theme_bw()
                       

```

```{r Gráfico Turbidez periodo1, warning = FALSE, message = FALSE}
(turb_p1 <- ggplot(plan_wide_19902020 %>% 
                     filter(ANO_COLETA>"1990" &
                              ANO_COLETA<="2000"),
                   aes(CODIGO,
                       Turbidez))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=100,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=40,
            ymax=100,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=40,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Turbidez no período 1990-2000",
        x="Estação",
        y="UNT")+
   scale_y_continuous(expand = expansion(mult = c(0.05, 0.03)),
                      n.breaks = 8,
                      limits = c(min(plan_wide_19902020$Turbidez, na.rm = TRUE),
                                 max(plan_wide_19902020$Turbidez, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Turbidez periodo2, warning = FALSE, message = FALSE}
(turb_p2 <- ggplot(plan_wide_19902020 %>% 
                     filter(ANO_COLETA>"2000" &
                              ANO_COLETA<="2010"),
                   aes(CODIGO,
                       Turbidez))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=100,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=40,
            ymax=100,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=40,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Turbidez no período 2000-2010",
        x="Estação",
        y="UNT")+
   scale_y_continuous(expand = expansion(mult = c(0.05, 0.03)),
                      n.breaks = 8,
                      limits = c(min(plan_wide_19902020$Turbidez, na.rm = TRUE),
                                 max(plan_wide_19902020$Turbidez, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico Turbidez periodo3, warning = FALSE, message = FALSE}
(turb_p3 <- ggplot(plan_wide_19902020 %>% 
                     filter(ANO_COLETA>"2010" &
                              ANO_COLETA<="2020"),
                   aes(CODIGO,
                       Turbidez))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=100,
            ymax=Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=40,
            ymax=100,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=0,
            ymax=40,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Turbidez no período 2010-2020",
        x="Estação",
        y="UNT")+
   scale_y_continuous(expand = expansion(mult = c(0.05, 0.03)),
                      n.breaks = 8,
                      limits = c(min(plan_wide_19902020$Turbidez, na.rm = TRUE),
                                 max(plan_wide_19902020$Turbidez, na.rm = TRUE)),
                      trans = "log10",
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico turb 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(turb_p1, turb_p2, turb_p3, ncol = 3)
```

```{r Sumário Turbidez, warning=FALSE, message = FALSE,}
(sum_turb_p1 <- plan_wide_19902020 %>%
   select(CODIGO, Turbidez, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(Turbidez, 
           na.rm = TRUE),
     q1 = 
       quantile(Turbidez, 0.25, 
                na.rm = TRUE),
     median = 
       median(Turbidez, 
              na.rm = TRUE),
     mean = 
       mean(Turbidez, 
            na.rm= TRUE),
     q3 = 
       quantile(Turbidez, 0.75, 
                na.rm = TRUE),
     max = 
       max(Turbidez, 
           na.rm = TRUE))
)

(sum_turb_p2 <- plan_wide_19902020 %>%
    select(CODIGO, Turbidez, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(Turbidez, 
            na.rm = TRUE),
      q1 = 
        quantile(Turbidez, 0.25, 
                 na.rm = TRUE),
      median = 
        median(Turbidez, 
               na.rm = TRUE),
      mean = 
        mean(Turbidez, 
             na.rm= TRUE),
      q3 = 
        quantile(Turbidez, 0.75, 
                 na.rm = TRUE),
      max = 
        max(Turbidez, 
            na.rm = TRUE))
)

(sum_turb_p3 <- plan_wide_19902020 %>%
    select(CODIGO, Turbidez, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(Turbidez, 
            na.rm = TRUE),
      q1 = 
        quantile(Turbidez, 0.25, 
                 na.rm = TRUE),
      median = 
        median(Turbidez, 
               na.rm = TRUE),
      mean = 
        mean(Turbidez, 
             na.rm= TRUE),
      q3 = 
        quantile(Turbidez, 0.75, 
                 na.rm = TRUE),
      max = 
        max(Turbidez, 
            na.rm = TRUE))
) 
```

```{r Salvando turb, warning=FALSE, message = FALSE,}
ggsave("turb.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = turb,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("turb_p1.png",
       plot = turb_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("turb_p2.png",
       plot = turb_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("turb_p3.png",
       plot = turb_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("turb_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(turb_p1, turb_p2, turb_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### pH

```{r Gráfico pH facetted, warning = FALSE, message = FALSE}
(pH <- ggplot(plan_wide_19902020,
                 aes(CODIGO,
                     pH))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=6,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=9,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=6,
            ymax=9,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
   labs(title = "pH no período 1990-2020",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                      n.breaks = 8,
                      limits = c(4,11),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico pH periodo1, warning = FALSE, message = FALSE}
(pH_p1 <- ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"1990" &
                            ANO_COLETA<="2000"),
                 aes(CODIGO,
                     pH))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=6,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=9,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=6,
            ymax=9,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "pH no período 1990-2000",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                      n.breaks = 8,
                      limits = c(4,11),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico pH periodo2, warning = FALSE, message = FALSE}
(pH_p2 <- ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"2000" &
                            ANO_COLETA<="2010"),
                 aes(CODIGO,
                     pH))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=6,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=9,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=6,
            ymax=9,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "pH no período 2000-2010",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                      n.breaks = 8,
                      limits = c(4,11),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico pH periodo3, warning = FALSE, message = FALSE}
(pH_p3 <- ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA>"2010" &
                            ANO_COLETA<="2020"),
                 aes(CODIGO,
                     pH))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=6,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=9,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=6,
            ymax=9,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "pH no período 2010-2020",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.01)),
                      n.breaks = 8,
                      limits = c(4,11),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico pH 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(pH_p1, pH_p2, pH_p3, ncol = 3)
```

```{r Sumário pH, warning=FALSE, message = FALSE,}
(sum_pH_p1 <- plan_wide_19902020 %>%
   select(CODIGO, pH, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(pH, 
           na.rm = TRUE),
     q1 = 
       quantile(pH, 0.25, 
                na.rm = TRUE),
     median = 
       median(pH, 
              na.rm = TRUE),
     mean = 
       mean(pH, 
            na.rm= TRUE),
     q3 = 
       quantile(pH, 0.75, 
                na.rm = TRUE),
     max = 
       max(pH, 
           na.rm = TRUE))
)

(sum_pH_p2 <- plan_wide_19902020 %>%
    select(CODIGO, pH, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(pH, 
            na.rm = TRUE),
      q1 = 
        quantile(pH, 0.25, 
                 na.rm = TRUE),
      median = 
        median(pH, 
               na.rm = TRUE),
      mean = 
        mean(pH, 
             na.rm= TRUE),
      q3 = 
        quantile(pH, 0.75, 
                 na.rm = TRUE),
      max = 
        max(pH, 
            na.rm = TRUE))
) 

(sum_pH_p3 <- plan_wide_19902020 %>%
    select(CODIGO, pH, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(pH, 
            na.rm = TRUE),
      q1 = 
        quantile(pH, 0.25, 
                 na.rm = TRUE),
      median = 
        median(pH, 
               na.rm = TRUE),
      mean = 
        mean(pH, 
             na.rm= TRUE),
      q3 = 
        quantile(pH, 0.75, 
                 na.rm = TRUE),
      max = 
        max(pH, 
            na.rm = TRUE))
)
```

```{r Salvando pH, warning=FALSE, message = FALSE,}
ggsave("pH.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = pH,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("pH_p1.png",
       plot = pH_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("pH_p2.png",
       plot = pH_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("pH_p3.png",
       plot = pH_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("pH_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(pH_p1, pH_p2, pH_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### Sólidos totais

```{r Gráfico SólTot facetted, warning = FALSE, message = FALSE}
(SolTot <- ggplot(plan_wide_19902020,
                  aes(CODIGO,
                      `Sólidos totais`))+
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 500, ymax = Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
   labs(title = "Sólidos totais no período 1990-2020",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$`Sólidos totais`, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico SólTot periodo1, warning = FALSE, message = FALSE}
(SolTot_p1 <- ggplot(plan_wide_19902020 %>% 
                       filter(ANO_COLETA>"1990" &
                                ANO_COLETA<="2000"),
                     aes(CODIGO,
                         `Sólidos totais`))+
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 500, ymax = Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Sólidos totais no período 1990-2000",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$`Sólidos totais`, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico SólTot periodo2, warning = FALSE, message = FALSE}
(SolTot_p2 <- ggplot(plan_wide_19902020 %>% 
                       filter(ANO_COLETA>"2000" &
                                ANO_COLETA<="2010"),
                     aes(CODIGO,
                         `Sólidos totais`))+
   annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 500, ymax = Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Sólidos totais no período 2000-2010",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$`Sólidos totais`, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
       size = 1.2,
       alpha = .25,
       width = .07,
    )+
    scale_x_discrete(limits = c("87398500", 
                                "87398980", 
                                "87398900", 
                                "87398950", 
                                "87405500", 
                                "87406900", 
                                "87409900"),
                     labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
    )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
    theme_grafs()
)
```

```{r Gráfico SólTot periodo3, warning = FALSE, message = FALSE}
(SolTot_p3 <- ggplot(plan_wide_19902020 %>% 
                        filter(ANO_COLETA>"2010" &
                                  ANO_COLETA<="2020"),
                     aes(CODIGO,
                         `Sólidos totais`))+
    annotate("rect",
            xmin = -Inf, xmax = Inf,
            ymin = 500, ymax = Inf,
            alpha=1,
            fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=500,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65))+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7)+
    labs(title = "Sólidos totais no período 2010-2020",
         x="Estação",
         y="")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$`Sólidos totais`, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico SólTot 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(SolTot_p1, SolTot_p2, SolTot_p3, ncol = 3)
```

```{r Sumário Sólidos Totais, warning=FALSE, message = FALSE,}
(sum_SolTot_p1 <- plan_wide_19902020 %>%
   select(CODIGO, `Sólidos totais`, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(`Sólidos totais`, 
           na.rm = TRUE),
     q1 = 
       quantile(`Sólidos totais`, 0.25, 
                na.rm = TRUE),
     median = 
       median(`Sólidos totais`, 
              na.rm = TRUE),
     mean = 
       mean(`Sólidos totais`, 
            na.rm= TRUE),
     q3 = 
       quantile(`Sólidos totais`, 0.75, 
                na.rm = TRUE),
     max = 
       max(`Sólidos totais`, 
           na.rm = TRUE))
)

(sum_SolTot_p2 <- plan_wide_19902020 %>%
    select(CODIGO, `Sólidos totais`, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(`Sólidos totais`, 
            na.rm = TRUE),
      q1 = 
        quantile(`Sólidos totais`, 0.25, 
                 na.rm = TRUE),
      median = 
        median(`Sólidos totais`, 
               na.rm = TRUE),
      mean = 
        mean(`Sólidos totais`, 
             na.rm= TRUE),
      q3 = 
        quantile(`Sólidos totais`, 0.75, 
                 na.rm = TRUE),
      max = 
        max(`Sólidos totais`, 
            na.rm = TRUE))
)

(sum_SolTot_p3 <- plan_wide_19902020 %>%
    select(CODIGO, `Sólidos totais`, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(`Sólidos totais`, 
            na.rm = TRUE),
      q1 = 
        quantile(`Sólidos totais`, 0.25, 
                 na.rm = TRUE),
      median = 
        median(`Sólidos totais`, 
               na.rm = TRUE),
      mean = 
        mean(`Sólidos totais`, 
             na.rm= TRUE),
      q3 = 
        quantile(`Sólidos totais`, 0.75, 
                 na.rm = TRUE),
      max = 
        max(`Sólidos totais`, 
            na.rm = TRUE))
)
```

```{r Salvando SolTot, warning=FALSE, message = FALSE,}
ggsave("SolTot.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = SolTot,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("SolTot_p1.png",
       plot = SolTot_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("SolTot_p2.png",
       plot = SolTot_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("SolTot_p3.png",
       plot = SolTot_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("SolTot_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(SolTot_p1, SolTot_p2, SolTot_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

### IQA

```{r Gráfico IQA facetted, echo = FALSE, message=FALSE, warning=FALSE}
(iqa <-ggplot(plan_wide_19902020,
              aes(CODIGO,
                  IQA, na.rm = TRUE))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=19,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=19,
            ymax=36,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=36,
            ymax=51,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=51,
            ymax=79,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=79,
            ymax=Inf,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65),
                na.rm = TRUE)+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7,
                na.rm = TRUE)+
   facet_wrap(~periodo)+
   labs(title = "Variação do IQA no período 1990-2020",
        x="Estação",
        y="IQA")+
   scale_y_continuous(expand = expansion(mult = c(0,0)),
                      n.breaks = 6,
                      limits = c(-1,101))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
   # theme(axis.title.y = element_blank())
)
```

```{r Gráfico IQA periodo1, echo = FALSE, message=FALSE, warning=FALSE}
(iqa_p1 <-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA > "1990" &
                            ANO_COLETA <= "2000"),
                 aes(CODIGO,
                     IQA, na.rm = TRUE))+
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=-Inf,
             ymax=19,
             alpha=1,
             fill="#ac5079")+ #>pior classe
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=19,
             ymax=36,
             alpha=1,
             fill="#eb5661")+ #classe 4
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=36,
             ymax=51,
             alpha=1,
             fill="#fcf7ab")+ #classe 3
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=51,
             ymax=79,
             alpha=1,
             fill="#70c18c")+ #classe 2
    annotate("rect",
             xmin=-Inf,
             xmax=Inf,
             ymin=79,
             ymax=Inf,
             alpha=1,
             fill="#8dcdeb")+ #classe 1
    stat_boxplot(geom = 'errorbar',
                 width=0.3,
                 position = position_dodge(width = 0.65),
                 na.rm = TRUE)+
    geom_boxplot(fill='#F8F8FF',
                 color="black",
                 outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                 width= 0.7,
                 na.rm = TRUE)+
    labs(title = "Variação do IQA no período 1990-2000",
         x="Estação",
         y="")+
    scale_y_continuous(expand = expansion(mult = c(0,0)),
                       n.breaks = 6,
                       limits = c(-1,101))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
    geom_smooth(method = "lm",
                se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
                aes(group=1),
                alpha=.5,
                na.rm = TRUE,
                size = 1)+
   theme_grafs()+
   theme(axis.title.y = element_blank())
)
```

```{r Gráfico IQA periodo2, echo = FALSE, message=FALSE, warning=FALSE}
(iqa_p2 <-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA > "2000" &
                            ANO_COLETA <= "2010"),
                 aes(CODIGO,
                     IQA, na.rm = TRUE))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=19,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=19,
            ymax=36,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=36,
            ymax=51,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=51,
            ymax=79,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=79,
            ymax=Inf,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65),
                na.rm = TRUE)+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7,
                na.rm = TRUE)+
   labs(title = "Variação do IQA no período 2000-2010",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0,0)),
                      n.breaks = 6,
                      limits = c(-1,101))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
 theme_grafs()+
   theme(axis.title.y = element_blank()
   )
)
```

```{r Gráfico IQA periodo3, echo = FALSE, message=FALSE, warning=FALSE}
(iqa_p3 <-ggplot(plan_wide_19902020 %>% 
                   filter(ANO_COLETA > "2010" &
                            ANO_COLETA <= "2020"),
                 aes(CODIGO,
                     IQA, na.rm = TRUE))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=19,
            alpha=1,
            fill="#ac5079")+ #>pior classe
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=19,
            ymax=36,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=36,
            ymax=51,
            alpha=1,
            fill="#fcf7ab")+ #classe 3
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=51,
            ymax=79,
            alpha=1,
            fill="#70c18c")+ #classe 2
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=79,
            ymax=Inf,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65),
                na.rm = TRUE)+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7,
                na.rm = TRUE)+
   labs(title = "Variação do IQA no período 2010-2020",
        x="Estação",
        y="")+
   scale_y_continuous(expand = expansion(mult = c(0,0)),
                      n.breaks = 6,
                      limits = c(-1,101))+
   ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
    theme_grafs()+
    theme(axis.title.y = element_blank())
)
```

```{r Gráfico IQA 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(iqa_p1, iqa_p2, iqa_p3, ncol = 3)
```

```{r Sumário IQA, warning=FALSE, message = FALSE,}
(sum_IQA_p1 <- plan_wide_19902020 %>%
   select(CODIGO, IQA, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(IQA, 
           na.rm = TRUE),
     q1 = 
       quantile(IQA, 0.25, 
                na.rm = TRUE),
     median = 
       median(IQA, 
              na.rm = TRUE),
     mean = 
       mean(IQA, 
            na.rm= TRUE),
     q3 = 
       quantile(IQA, 0.75, 
                na.rm = TRUE),
     max = 
       max(IQA, 
           na.rm = TRUE),
     n = 
        length(IQA)
   )
)

(sum_IQA_p2 <- plan_wide_19902020 %>%
    select(CODIGO, IQA, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(IQA, 
            na.rm = TRUE),
      q1 = 
        quantile(IQA, 0.25, 
                 na.rm = TRUE),
      median = 
        median(IQA, 
               na.rm = TRUE),
      mean = 
        mean(IQA, 
             na.rm= TRUE),
      q3 = 
        quantile(IQA, 0.75, 
                 na.rm = TRUE),
      max = 
        max(IQA, 
            na.rm = TRUE),
      n = 
        length(IQA)
      )
)

(sum_IQA_p3 <- plan_wide_19902020 %>%
    select(CODIGO, IQA, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>%
    # ?as_factor(CODIGO) %>% 
    group_by(CODIGO) %>%
    summarize(
      min = 
        min(IQA, 
            na.rm = TRUE),
      q1 = 
        quantile(IQA, 0.25, 
                 na.rm = TRUE),
      median = 
        median(IQA, 
               na.rm = TRUE),
      mean = 
        mean(IQA, 
             na.rm= TRUE),
      q3 = 
        quantile(IQA, 0.75, 
                 na.rm = TRUE),
      max = 
        max(IQA, 
            na.rm = TRUE),
      n = 
        length(IQA),
      NAs = 
        sum(is.na(IQA))
      ) %>% 
  mutate(
    "%NA" = NAs/n*100
  )
)

```

```{r Salvando iqa, warning=FALSE, message = FALSE,}
ggsave("iqa.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = iqa,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("iqa_p1.png",
       plot = iqa_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("iqa_p2.png",
       plot = iqa_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("iqa_p3.png",
       plot = iqa_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("iqa_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(iqa_p1, iqa_p2, iqa_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")
```

## Testando coisas

```{r Testando coisas, include = FALSE, warning=FALSE, message = FALSE,}
# plan_wide_19902020 %>% 
#    select(CODIGO, `Oxigênio dissolvido`, ANO_COLETA) %>% 
#    ggplot(aes(ANO_COLETA, `Oxigênio dissolvido`, 
#       col = CODIGO))+
#    geom_line()+
#    facet_wrap(~ CODIGO, ncol = 7)

# df111 <- data.frame(x = c(1:100))
# glimpse(df111)
# df111$y <- 2 + 3 * df111$x + rnorm(100, sd = 40)
# 
# lm_eqn <- function(df111){
#     m <- lm(y ~ x, df111);
#     eq <- substitute(y == a + b %.% x*","~~r^2~"="~r2,
#          list(a = format(unname(coef(m)[1]), digits = 2),
#               b = format(unname(coef(m)[2]), digits = 2),
#              r2 = format(summary(m)$r.squared, digits = 3)))
#     as.character(as.expression(eq));
# } 
# p2 <- p111 +
#   geom_text(x = 25, y = 300,
#             label = lm_eqn(df111),
#             parse = TRUE)
# p2
# 
# 
# lm_eqc <- function(plan_wide_19902020){
#    m <- lm(`Oxigênio dissolvido` ~ CODIGO, plan_wide_19902020);
#    eq <- substitute(y == a + b %.% x*","~~r^2~"="~r2,
#                     list(a = format(unname(coef(m)[1]), digits = 2),
#                          b = format(unname(coef(m)[2]), digits = 2),
#                          r2 = format(summary(m)$r.squared, digits = 3)))
#    as.character(as.expression(eq));
# }
# 
# (od_p1 <-ggplot(plan_wide_19902020 %>%
#                    filter(ANO_COLETA>"1990" &
#                              ANO_COLETA<="2000"),
#                 aes(CODIGO,
#                     `Oxigênio dissolvido`))+
#       annotate("rect",
#                xmin=-Inf,
#                xmax=Inf,
#                ymin=-Inf,
#                ymax=2,
#                alpha=1,
#                fill="#ac5079")+ #>pior classe
#       annotate("rect",
#                xmin=-Inf,
#                xmax=Inf,
#                ymin=2,
#                ymax=4,
#                alpha=1,
#                fill="#eb5661")+ #classe 4
#       annotate("rect",
#                xmin=-Inf,
#                xmax=Inf,
#                ymin=4,
#                ymax=5,
#                alpha=1,
#                fill="#fcf7ab")+ #classe 3
#       annotate("rect",
#                xmin=-Inf,
#                xmax=Inf,
#                ymin=5,
#                ymax=6,
#                alpha=1,
#                fill="#70c18c")+ #classe 2
#       annotate("rect",
#                xmin=-Inf,
#                xmax=Inf,
#                ymin=6,
#                ymax=Inf,
#                alpha=1,
#                fill="#8dcdeb")+ #classe 1
#       stat_boxplot(geom = 'errorbar',
#                    width=0.3,
#                    position = position_dodge(width = 0.65))+
#       geom_boxplot(fill='#F8F8FF',
#                    color="black",
#                    outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
#                    width= 0.7)+
#       labs(title = "Oxigênio Dissolvido no período 1990-2000",
#            x="Estação",
#            y="mg/L")+
#       # geom_jitter(width = .05,
#       #             alpha=.2,
#       #             size=1.5,
#       #             color="black")+
#       scale_y_continuous(expand = expansion(mult = c(0,0)),
#                          n.breaks = 11,
#                          limits = c(-1,21))+
#       scale_x_discrete(limits = c("87398500", "87398980", "87398900", "87398950", "87405500", "87406900", "87409900"))+
#       geom_smooth(method = "lm",
#                   se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
#                   aes(group=1),
#                   alpha=.5,
#                   na.rm = TRUE,
#                   size = 1)+
#       # annotate(geom_text(aes(x = "87405500", y = 15),
#       #                    label = lm_eqc(plan_wide_19902020),
#       #                    parse = TRUE,
#       #                    inherit.aes = TRUE,
#       #                    check_overlap = TRUE))+
#       #  geom_line(
#       #     aes(color="red"),
#       #     alpha=.0,
#       # )+
#       # scale_color_manual("Legenda",
#       #                    guide="legend",
#       #                    values = c("Classe 1"="#8dcdeb",
#       #                               "Classe 2"="#70c18c",
#       #                               "Classe 3"="#fcf7ab",
#       #                               "Classe 4"="#eb5661",
#       #                               "Pior Classe"="#ac5079"))+
#    # guides(color=guide_legend(override.aes = list(linetype=c(1,1,1,1,1),
#    #                                               lwd=c(2,2,2,2,2),
#    #                                               shape=c(NA,NA,NA,NA,NA),
#    #                                               alpha=1)))+
#       theme(legend.position = "bottom")+
#       theme_classic())

# list1111 <- sessionInfo()
# list1111$loadedOnly

# install.packages("ggpmisc")
# library(ggpmisc)

# summary(lm(plan_wide_19902020$CODIGO~plan_wide_19902020$DBO))
# 
# 
# p <- ggplot(data, aes(y=number, x=pod)) +
#   geom_boxplot()
# print(p)

# install.packages("GGally")


# fit = lm(plan_wide_19902020$`Oxigênio dissolvido`~ plan_wide_19902020$CODIGO)
# summary(fit)
# summary.lm(fit)
# 
# pacman::p_load(esquisse)

sumario <- function(x, y){
  x %>% 
    group_by(CODIGO) %>%
    summarise(
      list(min= ~min(., na.rm = TRUE), 
           Q1= ~quantile(., probs = 0.25),
           median= ~median(., na.rm = TRUE), 
           Q3= ~quantile(., probs = 0.75),
           max= ~max(., na.rm = TRUE)),
      .groups = "drop"
      )
}

plan_wide_19902020 %>% 
  select(CODIGO, `Oxigênio dissolvido`) %>% 
  sumario()  

parametros_IQA %>% 
  select(-CODIGO) %>% 
  # tail(n = 50) %>% 
  mutate(
    IQA_OD_quad = (`Oxigênio dissolvido`*0.17),
    IQA_Temp_quad = (if_else(`Temperatura água` != "", 1.58, 1.58)),
    IQA_Ecoli_quad = (parametros_IQA$`Escherichia coli`*0.15),
    IQA_pH_quad = (pH*0.12)
  ) %>% 
  summary(IQA_Temp_quad)
  # glimpse()
```

### Correlação

```{r Correlação, time_it = TRUE, warning=FALSE, message = FALSE,}
parametros_IQA %>% 
  select(-CODIGO) %>% 
  ggcorr(method = "complete.obs",
           # "pearson",
           # "pairwise",
         name = "Correlação",
         label = TRUE,
         label_alpha = TRUE,
         digits = 3,
         low = "#3B9AB2",
         mid = "#EEEEEE",
         high = "#F21A00",
         # palette = "RdYlBu",
         layout.exp = 0,
         legend.position = "left",
         label_round = 3,
         )

# Gráfico das correlações entre todos os parâmetros com significância
correl_IQA <- parametros_IQA %>%
  select(-CODIGO) %>%
  ggpairs(title = "Correlação entre parâmetros que compõem o IQA",
          axisLabels = "show")
```

### Condutividade elétrica
```{r Gráfico cond_elet facetted, warning = FALSE, message = FALSE}
(cond_elet <- ggplot(plan_wide_19902020,
                        aes(CODIGO,
                            Condutividade))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=500,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   facet_wrap(~periodo)+
      labs(title = "Condutividade elétrica no período 1990-2020",
        x="Estação",
        y="µmhos/cm")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico cond_elet periodo1, warning = FALSE, message = FALSE}
(cond_elet_p1 <- ggplot(plan_wide_19902020 %>% 
                          filter(ANO_COLETA>"2000" &
                                   ANO_COLETA<="2010"),
                        aes(CODIGO,
                            Condutividade))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=500,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
      labs(title = "Condutividade elétrica no período 1990-2000",
        x="Estação",
        y="µmhos/cm")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico cond_elet periodo2, warning = FALSE, message = FALSE}
(cond_elet_p2 <- ggplot(plan_wide_19902020 %>% 
                          filter(ANO_COLETA>"2000" &
                                   ANO_COLETA<="2010"),
                        aes(CODIGO,
                            Condutividade))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=500,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Condutividade elétrica no período 2000-2010",
        x="Estação",
        y="µmhos/cm")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico cond_elet periodo3, warning = FALSE, message = FALSE}
(cond_elet_p3 <- ggplot(plan_wide_19902020 %>% 
                          filter(ANO_COLETA>"2010" &
                                   ANO_COLETA<="2020"),
                        aes(CODIGO,
                            Condutividade))+
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=500,
            ymax=Inf,
            alpha=1,
            fill="#eb5661")+ #classe 4
   annotate("rect",
            xmin=-Inf,
            xmax=Inf,
            ymin=-Inf,
            ymax=500,
            alpha=1,
            fill="#8dcdeb")+ #classe 1
   stat_boxplot(geom = 'errorbar',
                width=0.3,
                position = position_dodge(width = 0.65))+
   geom_boxplot(fill='#F8F8FF',
                color="black",
                outlier.shape = NA, #se deixar NA fica só o jitter, se não, deixa 1
                width= 0.7)+
   labs(title = "Condutividade elétrica no período 2010-2020",
        x="Estação",
        y="µmhos/cm")+
   scale_y_continuous(expand = expansion(mult = c(0.01, 0.05)),
                      n.breaks = 8,
                      limits = c(0,
                                 max(plan_wide_19902020$Condutividade, na.rm = TRUE)),
                      labels = scales::number_format(accuracy = 1,
                                                     decimal.mark = ",",
                                                     big.mark = " "))+
    ggbeeswarm::geom_quasirandom(
     size = 1.2,
     alpha = .25,
     width = .07,
   )+
   scale_x_discrete(limits = c("87398500", 
                               "87398980", 
                               "87398900", 
                               "87398950", 
                               "87405500", 
                               "87406900", 
                               "87409900"),
                    labels = c("PM1", "PM2", "PM3", "PM4", "PM5", "PM6", "PM7")
   )+
   geom_smooth(method = "lm",
               se=FALSE, #se deixar TRUE gera o intervalo de confiança de 95%
               aes(group=1),
               alpha=.5,
               na.rm = TRUE,
               size = 1)+
   theme_grafs()
)
```

```{r Gráfico cond_elet 3 periodos juntos, warning=FALSE, message=FALSE}
grid.arrange(cond_elet_p1, cond_elet_p2, cond_elet_p3, ncol = 3)
```

```{r Sumário cond_elet, warning=FALSE, message = FALSE}
(sum_cond_elet_p1 <- plan_wide_19902020 %>%
   select(CODIGO, Condutividade, ANO_COLETA) %>% 
   filter(ANO_COLETA>"1990" &
            ANO_COLETA<="2000") %>% 
   group_by(CODIGO) %>% 
   summarize(
     min = 
       min(Condutividade, 
           na.rm = TRUE),
     q1 = 
       quantile(Condutividade, 0.25, 
                na.rm = TRUE),
     median = 
       median(Condutividade, 
              na.rm = TRUE),
     mean = 
       mean(Condutividade, 
            na.rm= TRUE),
     q3 = 
       quantile(Condutividade, 0.75, 
                na.rm = TRUE),
     max = 
       max(Condutividade, 
           na.rm = TRUE))
)

(sum_cond_elet_p2 <- plan_wide_19902020 %>%
    select(CODIGO, Condutividade, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2000" &
             ANO_COLETA<="2010") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(Condutividade, 
            na.rm = TRUE),
      q1 = 
        quantile(Condutividade, 0.25, 
                 na.rm = TRUE),
      median = 
        median(Condutividade, 
               na.rm = TRUE),
      mean = 
        mean(Condutividade, 
             na.rm= TRUE),
      q3 = 
        quantile(Condutividade, 0.75, 
                 na.rm = TRUE),
      max = 
        max(Condutividade, 
            na.rm = TRUE))
)

(sum_cond_elet_p3 <- plan_wide_19902020 %>%
    select(CODIGO, Condutividade, ANO_COLETA) %>% 
    filter(ANO_COLETA>"2010" &
             ANO_COLETA<="2020") %>% 
    group_by(CODIGO) %>% 
    summarize(
      min = 
        min(Condutividade, 
            na.rm = TRUE),
      q1 = 
        quantile(Condutividade, 0.25, 
                 na.rm = TRUE),
      median = 
        median(Condutividade, 
               na.rm = TRUE),
      mean = 
        mean(Condutividade, 
             na.rm= TRUE),
      q3 = 
        quantile(Condutividade, 0.75, 
                 na.rm = TRUE),
      max = 
        max(Condutividade, 
            na.rm = TRUE),
      n = 
        length(Condutividade))
)

# plan_wide_19902020 %>% 
#    select(CODIGO, IQA) %>% 
#    group_by(CODIGO) %>% 
#    summarize(
#       min = 
#          min(IQA, 
#              na.rm = TRUE),
#       q1 = 
#          quantile(IQA, 0.25, 
#                   na.rm = TRUE),
#       median = 
#          median(IQA, 
#                 na.rm = TRUE),
#       mean = 
#          mean(IQA, 
#               na.rm= TRUE),
#       q3 = 
#          quantile(IQA, 0.75, 
#                   na.rm = TRUE),
#       max = 
#          max(IQA, 
#              na.rm = TRUE))
```

```{r Salvando cond_elet, warning=FALSE, message = FALSE}
ggsave("cond_elet.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = cond_elet,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("cond_elet_p1.png",
       plot = cond_elet_p1,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("cond_elet_p2.png",
       plot = cond_elet_p2,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("cond_elet_p3.png",
       plot = cond_elet_p3,
       path = "./graficos",
       dpi = 300,
       type = "cairo")

ggsave("cond_elet_3periodos.png",
       units = c("px"),
       width = 4500,
       height = 2993,
       plot = grid.arrange(cond_elet_p1, cond_elet_p2, cond_elet_p3, ncol = 3),
       path = "./graficos",
       dpi = 300,
       type = "cairo")

```
